"rgb:10416772" - Search - Anna’s Archive

nexusstc/Python и машинное обучение: крайне необходимое пособие по новейшей предсказательной аналитике, обязательное для более глубокого понимания методологии машинного обучения/340062377a197db8759d0c6403c95255.pdf

Python и машинное обучение: крайне необходимое пособие по новейшей предсказательной аналитике, обязательное для более глубокого понимания методологии машинного обучения Себастьян Рашка; перевод с англ. А. В. Логунова Лань, Packt Publishing, Birmingham, UK, 2015

Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analyticsKey FeaturesLeverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualizationLearn effective strategies and best practices to improve and optimize machine learning systems and algorithmsAsk – and answer – tough questions of your data with robust statistical models, built for a range of datasetsBook DescriptionMachine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data – its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success. Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world's leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuring guidance and tips on everything from sentiment analysis to neural networks, you'll soon be able to answer some of the most important questions facing you and your organization. What you will learnExplore how to use different machine learning models to ask different questions of your dataLearn how to build neural networks using Keras and TheanoFind out how to write clean and elegant Python code that will optimize the strength of your algorithmsDiscover how to embed your machine learning model in a web application for increased accessibilityPredict continuous target outcomes using regression analysisUncover hidden patterns and structures in data with clusteringOrganize data using effective pre-processing techniquesGet to grips with sentiment analysis to delve deeper into textual and social media dataWho this book is forIf you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource.

Russian [ru] · English [en] · PDF · 75.4MB · 2015 · 📘 Book (non-fiction) · 🚀/lgli/lgrs/nexusstc/zlib · Save

nexusstc/Python 机器学习/a10e2f24433a12cbd9b60d22e82aaaff.epub

Python 机器学习 it-ebooks iBooker it-ebooks, it-ebooks-2017, 2017

Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analyticsKey FeaturesLeverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualizationLearn effective strategies and best practices to improve and optimize machine learning systems and algorithmsAsk – and answer – tough questions of your data with robust statistical models, built for a range of datasetsBook DescriptionMachine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data – its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success. Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world's leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuring guidance and tips on everything from sentiment analysis to neural networks, you'll soon be able to answer some of the most important questions facing you and your organization. What you will learnExplore how to use different machine learning models to ask different questions of your dataLearn how to build neural networks using Keras and TheanoFind out how to write clean and elegant Python code that will optimize the strength of your algorithmsDiscover how to embed your machine learning model in a web application for increased accessibilityPredict continuous target outcomes using regression analysisUncover hidden patterns and structures in data with clusteringOrganize data using effective pre-processing techniquesGet to grips with sentiment analysis to delve deeper into textual and social media dataWho this book is forIf you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource.

English [en] · Chinese [zh] · EPUB · 6.2MB · 2017 · 📘 Book (non-fiction) · 🚀/lgli/lgrs/nexusstc/zlib · Save

upload/duxiu_main2/【星空藏书馆】/【星空藏书馆】等多个文件/Kindle电子书库（012）/综合书籍（007）/综合1（011）/书1/yanhu831/Verycd Share/Packt/2015/Packt.Python.Machine.Learning.2015.9.pdf

Python machine learning : unlock deeper insights into machine learning with this vital guide to cutting-edge predictive analytics Sebastian Raschka Packt Publishing Limited, Packt Publishing, Birmingham, UK, 2015

Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics About This Book <ul> <li>Leverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualization </li> <li>Learn effective strategies and best practices to improve and optimize machine learning systems and algorithms </li> <li>Ask – and answer – tough questions of your data with robust statistical models, built for a range of datasets </li></ul>Who This Book Is For If you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource. What You Will Learn <ul> <li>Explore how to use different machine learning models to ask different questions of your data </li> <li>Learn how to build neural networks using Keras and Theano </li> <li>Find out how to write clean and elegant Python code that will optimize the strength of your algorithms </li> <li>Discover how to embed your machine learning model in a web application for increased accessibility </li> <li>Predict continuous target outcomes using regression analysis </li> <li>Uncover hidden patterns and structures in data with clustering </li> <li>Organize data using effective pre-processing techniques </li> <li>Get to grips with sentiment analysis to delve deeper into textual and social media data </li></ul>In Detail Machine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data – its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success. Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world's leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuring guidance and tips on everything from sentiment analysis to neural networks, you'll soon be able to answer some of the most important questions facing you and your organization. Style and approach Python Machine Learning connects the fundamental theoretical principles behind machine learning to their practical application in a way that focuses you on asking and answering the right questions. It walks you through the key elements of Python and its powerful machine learning libraries, while demonstrating how to get to grips with a range of statistical models.

English [en] · PDF · 10.2MB · 2015 · 📘 Book (non-fiction) · 🚀/lgli/lgrs/nexusstc/upload/zlib · Save

upload/bibliotik/0_Other/2/2015 Sebastian Raschka - Python Machine Learning_Rxl.pdf

Python machine learning : unlock deeper insights into machine learning with this vital guide to cutting-edge predictive analytics Raschka, Sebastian Packt Publishing Limited, Packt Publishing, Birmingham, UK, 2015

Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics About This Book <ul> <li>Leverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualization </li> <li>Learn effective strategies and best practices to improve and optimize machine learning systems and algorithms </li> <li>Ask – and answer – tough questions of your data with robust statistical models, built for a range of datasets </li></ul>Who This Book Is For If you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource. What You Will Learn <ul> <li>Explore how to use different machine learning models to ask different questions of your data </li> <li>Learn how to build neural networks using Keras and Theano </li> <li>Find out how to write clean and elegant Python code that will optimize the strength of your algorithms </li> <li>Discover how to embed your machine learning model in a web application for increased accessibility </li> <li>Predict continuous target outcomes using regression analysis </li> <li>Uncover hidden patterns and structures in data with clustering </li> <li>Organize data using effective pre-processing techniques </li> <li>Get to grips with sentiment analysis to delve deeper into textual and social media data </li></ul>In Detail Machine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data – its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success. Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world's leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuring guidance and tips on everything from sentiment analysis to neural networks, you'll soon be able to answer some of the most important questions facing you and your organization. Style and approach Python Machine Learning connects the fundamental theoretical principles behind machine learning to their practical application in a way that focuses you on asking and answering the right questions. It walks you through the key elements of Python and its powerful machine learning libraries, while demonstrating how to get to grips with a range of statistical models.

English [en] · PDF · 10.1MB · 2015 · 📘 Book (non-fiction) · 🚀/lgli/lgrs/nexusstc/upload/zlib · Save

upload/trantor/en/Beyeler, Michael/Machine Learning for OpenCV.epub

Machine Learning for OpenCV : Expand Your OpenCV Knowledge and Master Key Concepts of Machine Learning Using This Practical, Hands-on Guide. Beyeler, Michael Packt Publishing Limited, Packt Publishing, Birmingham, UK, 2015

Link to the GitHub Repository containing the code examples and additionalmaterial: [ of the most innovative breakthroughs and exciting new technologies can beattributed to applications of machine learning. We are living in an age wheredata comes in abundance, and thanks to the self-learning algorithms from thefield of machine learning, we can turn this data into knowledge. Automatedspeech recognition on our smart phones, web search engines, e-mail spamfilters, the recommendation systems of our favorite movie streaming services –machine learning makes it all possible.Thanks to the many powerful open-source libraries that have been developed inrecent years, machine learning is now right at our fingertips. Python providesthe perfect environment to build machine learning systems productively.This book will teach you the fundamentals of machine learning and how toutilize these in real-world applications using Python. Step-by-step, you willexpand your skill set with the best practices for transforming raw data intouseful information, developing learning algorithms efficiently, and evaluatingresults.You will discover the different problem categories that machine learning cansolve and explore how to classify objects, predict continuous outcomes withregression analysis, and find hidden structures in data via clustering. Youwill build your own machine learning system for sentiment analysis andfinally, learn how to embed your model into a web app to share with the worldwords : 87138

English [en] · EPUB · 28.0MB · 2015 · 📗 Book (unknown) · 🚀/upload/zlib · Save

lgli/r:\!fiction\0day\1\Machine Learning for OpenCV 4, 2nd ed. - Beyeler,Sharma,Shrimali (Packt Publishing;2019;9781789536300;eng).epub

Machine Learning for OpenCV 4 : Intelligent Algorithms for Building Image Processing Apps Using OpenCV 4, Python, and Scikit-learn, 2nd Edition Beyeler, Michael;Sharma, Aditya;Vishwesh Ravi Shrimali Packt Publishing, Limited; Packt Publishing, 2nd ed, Place of publication not identified, 2019

A practical guide to understanding the core machine learning and deep learning algorithms, and implementing them to create intelligent image processing systems using OpenCV 4 Key Features Gain insights into machine learning algorithms, and implement them using OpenCV 4 and scikit-learn Get up to speed with Intel OpenVINO and its integration with OpenCV 4 Implement high-performance machine learning models with helpful tips and best practices Book Description OpenCV is an opensource library for building computer vision apps. The latest release, OpenCV 4, offers a plethora of features and platform improvements that are covered comprehensively in this up-to-date second edition. You'll start by understanding the new features and setting up OpenCV 4 to build your computer vision applications. You will explore the fundamentals of machine learning and even learn to design different algorithms that can be used for image processing. Gradually, the book will take you through supervised and unsupervised machine learning. You will gain hands-on experience using scikit-learn in Python for a variety of machine learning applications. Later chapters will focus on different machine learning algorithms, such as a decision tree, support vector machines (SVM), and Bayesian learning, and how they can be used for object detection computer vision operations. You will then delve into deep learning and ensemble learning, and discover their real-world applications, such as handwritten digit classification and gesture recognition. Finally, you'll get to grips with the latest Intel OpenVINO for building an image processing system. By the end of this book, you will have developed the skills you need to use machine learning for building intelligent computer vision applications with OpenCV 4. What you will learn Understand the core machine learning concepts for image processing Explore the theory behind machine learning and deep learning algorithm design Discover effective techniques to train your deep learning models Evaluate machine learning models to improve the performance of your models Integrate algorithms such as support vector machines and Bayes classifier in your computer vision applications Use OpenVINO with OpenCV 4 to speed up model inference Who this book is for This book is for Computer Vision professionals, machine learning developers, or anyone who wants to learn machine learning algorithms and implement them using OpenCV 4. If you want to build real-world Co...

English [en] · EPUB · 13.3MB · 2019 · 📘 Book (non-fiction) · 🚀/lgli/lgrs/nexusstc/zlib · Save

zlib/no-category/Sebastian Raschka/Python Machine Learning_117993858.pdf

Python Machine Learning : Learn How to Build Powerful Python Machine Learning Algorithms to Generate Useful Data Insights with This Data Analysis Tutorial Sebastian Raschka Packt Publishing Limited, Packt Publishing, Birmingham, UK, 2015

Link to the GitHub Repository containing the code examples and additional material: Many of the most innovative breakthroughs and exciting new technologies can be attributed to applications of machine learning. We are living in an age where data comes in abundance, and thanks to the self-learning algorithms from the field of machine learning, we can turn this data into knowledge. Automated speech recognition on our smart phones, web search engines, e-mail spam filters, the recommendation systems of our favorite movie streaming services – machine learning makes it all possible. Thanks to the many powerful open-source libraries that have been developed in recent years, machine learning is now right at our fingertips. Python provides the perfect environment to build machine learning systems productively. This book will teach you the fundamentals of machine learning and how to utilize these in real-world applications using Python. Step-by-step, you will expand your skill set with the best practices for transforming raw data into useful information, developing learning algorithms efficiently, and evaluating results. You will discover the different problem categories that machine learning can solve and explore how to classify objects, predict continuous outcomes with regression analysis, and find hidden structures in data via clustering. You will build your own machine learning system for sentiment analysis and finally, learn how to embed your model into a web app to share with the worldISBN : 9781783555130

English [en] · PDF · 25.1MB · 2015 · 📗 Book (unknown) · 🚀/zlib · Save

zlib/no-category/Sebastian Raschka/Python Machine Learning_115128709.pdf

Python Machine Learning : Learn How to Build Powerful Python Machine Learning Algorithms to Generate Useful Data Insights with This Data Analysis Tutorial Sebastian Raschka Packt Publishing Limited, 1, 1, 2015

Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics About This Book <ul> <li>Leverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualization </li> <li>Learn effective strategies and best practices to improve and optimize machine learning systems and algorithms </li> <li>Ask – and answer – tough questions of your data with robust statistical models, built for a range of datasets </li></ul>Who This Book Is For If you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource. What You Will Learn <ul> <li>Explore how to use different machine learning models to ask different questions of your data </li> <li>Learn how to build neural networks using Keras and Theano </li> <li>Find out how to write clean and elegant Python code that will optimize the strength of your algorithms </li> <li>Discover how to embed your machine learning model in a web application for increased accessibility </li> <li>Predict continuous target outcomes using regression analysis </li> <li>Uncover hidden patterns and structures in data with clustering </li> <li>Organize data using effective pre-processing techniques </li> <li>Get to grips with sentiment analysis to delve deeper into textual and social media data </li></ul>In Detail Machine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data – its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success. Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world's leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuring guidance and tips on everything from sentiment analysis to neural networks, you'll soon be able to answer some of the most important questions facing you and your organization. Style and approach Python Machine Learning connects the fundamental theoretical principles behind machine learning to their practical application in a way that focuses you on asking and answering the right questions. It walks you through the key elements of Python and its powerful machine learning libraries, while demonstrating how to get to grips with a range of statistical models.

English [en] · PDF · 12.0MB · 2015 · 📗 Book (unknown) · 🚀/zlib · Save

zlib/no-category/Sebastian Raschka/Python Machine Learning_117993859.epub

Python Machine Learning : Learn How to Build Powerful Python Machine Learning Algorithms to Generate Useful Data Insights with This Data Analysis Tutorial Sebastian Raschka Packt Publishing Limited, Packt Publishing, Birmingham, UK, 2015

Link to the GitHub Repository containing the code examples and additional material: Many of the most innovative breakthroughs and exciting new technologies can be attributed to applications of machine learning. We are living in an age where data comes in abundance, and thanks to the self-learning algorithms from the field of machine learning, we can turn this data into knowledge. Automated speech recognition on our smart phones, web search engines, e-mail spam filters, the recommendation systems of our favorite movie streaming services – machine learning makes it all possible. Thanks to the many powerful open-source libraries that have been developed in recent years, machine learning is now right at our fingertips. Python provides the perfect environment to build machine learning systems productively. This book will teach you the fundamentals of machine learning and how to utilize these in real-world applications using Python. Step-by-step, you will expand your skill set with the best practices for transforming raw data into useful information, developing learning algorithms efficiently, and evaluating results. You will discover the different problem categories that machine learning can solve and explore how to classify objects, predict continuous outcomes with regression analysis, and find hidden structures in data via clustering. You will build your own machine learning system for sentiment analysis and finally, learn how to embed your model into a web app to share with the worldISBN : 9781783555130

English [en] · EPUB · 22.8MB · 2015 · 📗 Book (unknown) · 🚀/zlib · Save

lgli/Sebastian Raschka - Python Machine Learning: Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics (2015, ).pdf

Python machine learning : unlock deeper insights into machine learning with this vital guide to cutting-edge predictive analytics Sebastian Raschka Packt Publishing Limited, Packt Publishing, Birmingham, UK, 2015

Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics About This Book <ul> <li>Leverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualization </li> <li>Learn effective strategies and best practices to improve and optimize machine learning systems and algorithms </li> <li>Ask – and answer – tough questions of your data with robust statistical models, built for a range of datasets </li></ul>Who This Book Is For If you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource. What You Will Learn <ul> <li>Explore how to use different machine learning models to ask different questions of your data </li> <li>Learn how to build neural networks using Keras and Theano </li> <li>Find out how to write clean and elegant Python code that will optimize the strength of your algorithms </li> <li>Discover how to embed your machine learning model in a web application for increased accessibility </li> <li>Predict continuous target outcomes using regression analysis </li> <li>Uncover hidden patterns and structures in data with clustering </li> <li>Organize data using effective pre-processing techniques </li> <li>Get to grips with sentiment analysis to delve deeper into textual and social media data </li></ul>In Detail Machine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data – its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success. Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world's leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuring guidance and tips on everything from sentiment analysis to neural networks, you'll soon be able to answer some of the most important questions facing you and your organization. Style and approach Python Machine Learning connects the fundamental theoretical principles behind machine learning to their practical application in a way that focuses you on asking and answering the right questions. It walks you through the key elements of Python and its powerful machine learning libraries, while demonstrating how to get to grips with a range of statistical models.

English [en] · PDF · 35.3MB · 2015 · 📘 Book (non-fiction) · 🚀/lgli/zlib · Save

upload/newsarch_ebooks/2018/09/01/1783555130.pdf

Machine Learning con Python: costruire algoritmi per generare conoscenza Sebastian Raschka Feltrinelli Editore;Apogeo, Master, 2018;2017

Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics About This Book <ul> <li>Leverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualization </li> <li>Learn effective strategies and best practices to improve and optimize machine learning systems and algorithms </li> <li>Ask – and answer – tough questions of your data with robust statistical models, built for a range of datasets </li></ul>Who This Book Is For If you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource. What You Will Learn <ul> <li>Explore how to use different machine learning models to ask different questions of your data </li> <li>Learn how to build neural networks using Keras and Theano </li> <li>Find out how to write clean and elegant Python code that will optimize the strength of your algorithms </li> <li>Discover how to embed your machine learning model in a web application for increased accessibility </li> <li>Predict continuous target outcomes using regression analysis </li> <li>Uncover hidden patterns and structures in data with clustering </li> <li>Organize data using effective pre-processing techniques </li> <li>Get to grips with sentiment analysis to delve deeper into textual and social media data </li></ul>In Detail Machine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data – its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success. Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world's leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuring guidance and tips on everything from sentiment analysis to neural networks, you'll soon be able to answer some of the most important questions facing you and your organization. Style and approach Python Machine Learning connects the fundamental theoretical principles behind machine learning to their practical application in a way that focuses you on asking and answering the right questions. It walks you through the key elements of Python and its powerful machine learning libraries, while demonstrating how to get to grips with a range of statistical models.

English [en] · PDF · 16.4MB · 2015 · 📘 Book (non-fiction) · 🚀/lgli/upload/zlib · Save

ia/pythonmachinelea0000rasc.pdf

Python Machine Learning : Learn How to Build Powerful Python Machine Learning Algorithms to Generate Useful Data Insights with This Data Analysis Tutorial Sebastian Raschka Birmingham, UK: Packt Publishing Ltd., Packt Publishing, Birmingham, UK, 2015

Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analyticsKey FeaturesLeverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualizationLearn effective strategies and best practices to improve and optimize machine learning systems and algorithmsAsk – and answer – tough questions of your data with robust statistical models, built for a range of datasetsBook DescriptionMachine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data – its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success. Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world's leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuring guidance and tips on everything from sentiment analysis to neural networks, you'll soon be able to answer some of the most important questions facing you and your organization. What you will learnExplore how to use different machine learning models to ask different questions of your dataLearn how to build neural networks using Keras and TheanoFind out how to write clean and elegant Python code that will optimize the strength of your algorithmsDiscover how to embed your machine learning model in a web application for increased accessibilityPredict continuous target outcomes using regression analysisUncover hidden patterns and structures in data with clusteringOrganize data using effective pre-processing techniquesGet to grips with sentiment analysis to delve deeper into textual and social media dataWho this book is forIf you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource.

English [en] · PDF · 23.2MB · 2015 · 📗 Book (unknown) · 🚀/ia · Save

lgli/I:\it-books_dl\4000\Python Machine Learning.pdf

Python machine learning : unlock deeper insights into machine learning with this vital guide to cutting-edge predictive analytics Sebastian Raschka Packt Publishing Limited, Packt Publishing, Birmingham, UK, 2015

Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics About This Book <ul> <li>Leverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualization </li> <li>Learn effective strategies and best practices to improve and optimize machine learning systems and algorithms </li> <li>Ask – and answer – tough questions of your data with robust statistical models, built for a range of datasets </li></ul>Who This Book Is For If you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource. What You Will Learn <ul> <li>Explore how to use different machine learning models to ask different questions of your data </li> <li>Learn how to build neural networks using Keras and Theano </li> <li>Find out how to write clean and elegant Python code that will optimize the strength of your algorithms </li> <li>Discover how to embed your machine learning model in a web application for increased accessibility </li> <li>Predict continuous target outcomes using regression analysis </li> <li>Uncover hidden patterns and structures in data with clustering </li> <li>Organize data using effective pre-processing techniques </li> <li>Get to grips with sentiment analysis to delve deeper into textual and social media data </li></ul>In Detail Machine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data – its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success. Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world's leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuring guidance and tips on everything from sentiment analysis to neural networks, you'll soon be able to answer some of the most important questions facing you and your organization. Style and approach Python Machine Learning connects the fundamental theoretical principles behind machine learning to their practical application in a way that focuses you on asking and answering the right questions. It walks you through the key elements of Python and its powerful machine learning libraries, while demonstrating how to get to grips with a range of statistical models.

English [en] · PDF · 34.8MB · 2015 · 📘 Book (non-fiction) · 🚀/lgli/lgrs/nexusstc/zlib · Save

upload/duxiu_main2/【大学堂图书馆】/【大学堂40T教程】等多个文件/【02】epubee全站/【24】/e8/PythonMachineLearning.epub

Machine Learning con Python: costruire algoritmi per generare conoscenza Sebastian Raschka Feltrinelli Editore;Apogeo, Master, 2018;2017

Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analyticsAbout This BookLeverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualizationLearn effective strategies and best practices to improve and optimize machine learning systems and algorithmsAsk - and answer - tough questions of your data with robust statistical models, built for a range of datasetsWho This Book Is ForIf you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning - whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource. What You Will LearnExplore how to use different machine learning models to ask different questions of your dataLearn how to build neural networks using Pylearn 2 and TheanoFind out how to write clean and elegant Python code that will optimize the strength of your algorithmsDiscover how to embed your machine learning model in a web application for increased accessibilityPredict continuous target outcomes using regression analysisUncover hidden patterns and structures in data with clusteringOrganize data using effective pre-processing techniquesGet to grips with sentiment analysis to delve deeper into textual and social media dataIn DetailMachine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data - its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success. Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world's leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Pylearn2, and featuring guidance and tips on everything from sentiment analysis to neural networks, you'll soon be able to answer some of the most important questions facing you and your organization. Style and approachPython Machine Learning connects the fundamental theoretical principles behind machine learning to their practical application in a way that focuses you on asking and answering the right questions. It walks you through the key elements of Python and its powerful machine learning libraries, while demonstrating how to get to grips with a range of statistical models

English [en] · EPUB · 17.7MB · 2015 · 📘 Book (non-fiction) · 🚀/lgli/upload/zlib · Save

lgli/Z:\Bibliotik_\A Library\Machine Learning\Python Machine Learning\Python Machine Learning.pdf

Python machine learning : unlock deeper insights into machine learning with this vital guide to cutting-edge predictive analytics Raschka, Sebastian Packt Publishing Limited, Packt Publishing, Birmingham, UK, 2015

Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics About This Book <ul> <li>Leverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualization </li> <li>Learn effective strategies and best practices to improve and optimize machine learning systems and algorithms </li> <li>Ask – and answer – tough questions of your data with robust statistical models, built for a range of datasets </li></ul>Who This Book Is For If you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource. What You Will Learn <ul> <li>Explore how to use different machine learning models to ask different questions of your data </li> <li>Learn how to build neural networks using Keras and Theano </li> <li>Find out how to write clean and elegant Python code that will optimize the strength of your algorithms </li> <li>Discover how to embed your machine learning model in a web application for increased accessibility </li> <li>Predict continuous target outcomes using regression analysis </li> <li>Uncover hidden patterns and structures in data with clustering </li> <li>Organize data using effective pre-processing techniques </li> <li>Get to grips with sentiment analysis to delve deeper into textual and social media data </li></ul>In Detail Machine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data – its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success. Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world's leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuring guidance and tips on everything from sentiment analysis to neural networks, you'll soon be able to answer some of the most important questions facing you and your organization. Style and approach Python Machine Learning connects the fundamental theoretical principles behind machine learning to their practical application in a way that focuses you on asking and answering the right questions. It walks you through the key elements of Python and its powerful machine learning libraries, while demonstrating how to get to grips with a range of statistical models.

English [en] · PDF · 34.8MB · 2015 · 📘 Book (non-fiction) · 🚀/lgli/lgrs/nexusstc/zlib · Save

lgli/F:\!upload\_books\Python Deeper Insights into Machine Learning.epub

Python machine learning : unlock deeper insights into machine learning with this vital guide to cutting-edge predictive analytics John Hearty, David Julian, Sebastian Raschka Packt Publishing Limited, Community experience distilled, Birmingham, UK, 2015

Machine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data - its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success. Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world's leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Pylearn2, and featuring guidance and tips on everything from sentiment analysis to neural networks, you'll soon be able to answer some of the most important questions facing you and your organization. Read more... Abstract: Machine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data - its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success. Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world's leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Pylearn2, and featuring guidance and tips on everything from sentiment analysis to neural networks, you'll soon be able to answer some of the most important questions facing you and your organization

English [en] · EPUB · 24.3MB · 2015 · 📘 Book (non-fiction) · 🚀/lgli/lgrs/nexusstc/zlib · Save

nexusstc/Python Machine Learning: Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics/176aab57e875a95795c900e624f2b222.pdf

Python machine learning : unlock deeper insights into machine learning with this vital guide to cutting-edge predictive analytics Sebastian Raschka Packt Publishing Limited, Packt Publishing, Birmingham, UK, 2015

Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics About This Book <ul> <li>Leverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualization </li> <li>Learn effective strategies and best practices to improve and optimize machine learning systems and algorithms </li> <li>Ask – and answer – tough questions of your data with robust statistical models, built for a range of datasets </li></ul>Who This Book Is For If you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource. What You Will Learn <ul> <li>Explore how to use different machine learning models to ask different questions of your data </li> <li>Learn how to build neural networks using Keras and Theano </li> <li>Find out how to write clean and elegant Python code that will optimize the strength of your algorithms </li> <li>Discover how to embed your machine learning model in a web application for increased accessibility </li> <li>Predict continuous target outcomes using regression analysis </li> <li>Uncover hidden patterns and structures in data with clustering </li> <li>Organize data using effective pre-processing techniques </li> <li>Get to grips with sentiment analysis to delve deeper into textual and social media data </li></ul>In Detail Machine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data – its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success. Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world's leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuring guidance and tips on everything from sentiment analysis to neural networks, you'll soon be able to answer some of the most important questions facing you and your organization. Style and approach Python Machine Learning connects the fundamental theoretical principles behind machine learning to their practical application in a way that focuses you on asking and answering the right questions. It walks you through the key elements of Python and its powerful machine learning libraries, while demonstrating how to get to grips with a range of statistical models.

English [en] · PDF · 10.2MB · 2015 · 📘 Book (non-fiction) · 🚀/lgli/lgrs/nexusstc/zlib · Save

upload/newsarch_ebooks_2025_10/2019/01/29/1783555130.epub

Python machine learning : unlock deeper insights into machine learning with this vital guide to cutting-edge predictive analytics Raschka, Sebastian Packt Publishing Limited, Packt Publishing, Birmingham, UK, 2015

Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics About This Book <ul> <li>Leverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualization </li> <li>Learn effective strategies and best practices to improve and optimize machine learning systems and algorithms </li> <li>Ask – and answer – tough questions of your data with robust statistical models, built for a range of datasets </li></ul>Who This Book Is For If you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource. What You Will Learn <ul> <li>Explore how to use different machine learning models to ask different questions of your data </li> <li>Learn how to build neural networks using Keras and Theano </li> <li>Find out how to write clean and elegant Python code that will optimize the strength of your algorithms </li> <li>Discover how to embed your machine learning model in a web application for increased accessibility </li> <li>Predict continuous target outcomes using regression analysis </li> <li>Uncover hidden patterns and structures in data with clustering </li> <li>Organize data using effective pre-processing techniques </li> <li>Get to grips with sentiment analysis to delve deeper into textual and social media data </li></ul>In Detail Machine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data – its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success. Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world's leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuring guidance and tips on everything from sentiment analysis to neural networks, you'll soon be able to answer some of the most important questions facing you and your organization. Style and approach Python Machine Learning connects the fundamental theoretical principles behind machine learning to their practical application in a way that focuses you on asking and answering the right questions. It walks you through the key elements of Python and its powerful machine learning libraries, while demonstrating how to get to grips with a range of statistical models.

English [en] · EPUB · 17.6MB · 2015 · 📘 Book (non-fiction) · 🚀/lgli/lgrs/nexusstc/upload/zlib · Save

upload/bibliotik/0_Other/2/2015 Sebastian Raschka - Python Machine Learning_Rxl.azw3

Python machine learning : unlock deeper insights into machine learning with this vital guide to cutting-edge predictive analytics Raschka, Sebastian Packt Publishing Limited, Packt Publishing, Birmingham, UK, 2015

Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics About This Book <ul> <li>Leverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualization </li> <li>Learn effective strategies and best practices to improve and optimize machine learning systems and algorithms </li> <li>Ask – and answer – tough questions of your data with robust statistical models, built for a range of datasets </li></ul>Who This Book Is For If you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource. What You Will Learn <ul> <li>Explore how to use different machine learning models to ask different questions of your data </li> <li>Learn how to build neural networks using Keras and Theano </li> <li>Find out how to write clean and elegant Python code that will optimize the strength of your algorithms </li> <li>Discover how to embed your machine learning model in a web application for increased accessibility </li> <li>Predict continuous target outcomes using regression analysis </li> <li>Uncover hidden patterns and structures in data with clustering </li> <li>Organize data using effective pre-processing techniques </li> <li>Get to grips with sentiment analysis to delve deeper into textual and social media data </li></ul>In Detail Machine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data – its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success. Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world's leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuring guidance and tips on everything from sentiment analysis to neural networks, you'll soon be able to answer some of the most important questions facing you and your organization. Style and approach Python Machine Learning connects the fundamental theoretical principles behind machine learning to their practical application in a way that focuses you on asking and answering the right questions. It walks you through the key elements of Python and its powerful machine learning libraries, while demonstrating how to get to grips with a range of statistical models.

English [en] · AZW3 · 14.9MB · 2015 · 📘 Book (non-fiction) · 🚀/lgli/lgrs/nexusstc/upload/zlib · Save

upload/newsarch_ebooks_2025_10/2017/09/16/extracted__Python Machine Learning.mobi.zip/Python Machine Learning.mobi

Python machine learning : unlock deeper insights into machine learning with this vital guide to cutting-edge predictive analytics Raschka, Sebastian Packt Publishing Limited, Packt Publishing, Birmingham, UK, 2015

Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics About This Book <ul> <li>Leverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualization </li> <li>Learn effective strategies and best practices to improve and optimize machine learning systems and algorithms </li> <li>Ask – and answer – tough questions of your data with robust statistical models, built for a range of datasets </li></ul>Who This Book Is For If you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource. What You Will Learn <ul> <li>Explore how to use different machine learning models to ask different questions of your data </li> <li>Learn how to build neural networks using Keras and Theano </li> <li>Find out how to write clean and elegant Python code that will optimize the strength of your algorithms </li> <li>Discover how to embed your machine learning model in a web application for increased accessibility </li> <li>Predict continuous target outcomes using regression analysis </li> <li>Uncover hidden patterns and structures in data with clustering </li> <li>Organize data using effective pre-processing techniques </li> <li>Get to grips with sentiment analysis to delve deeper into textual and social media data </li></ul>In Detail Machine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data – its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success. Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world's leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuring guidance and tips on everything from sentiment analysis to neural networks, you'll soon be able to answer some of the most important questions facing you and your organization. Style and approach Python Machine Learning connects the fundamental theoretical principles behind machine learning to their practical application in a way that focuses you on asking and answering the right questions. It walks you through the key elements of Python and its powerful machine learning libraries, while demonstrating how to get to grips with a range of statistical models.

English [en] · MOBI · 26.4MB · 2015 · 📘 Book (non-fiction) · 🚀/lgli/lgrs/nexusstc/upload/zlib · Save

upload/duxiu_main2/【星空藏书馆】/【星空藏书馆】等多个文件/Kindle电子书库（012）/综合书籍（007）/综合1（011）/书1/yanhu831/Verycd Share/Packt/2015/Packt.Python.Machine.Learning.2015.9.epub

Python machine learning : unlock deeper insights into machine learning with this vital guide to cutting-edge predictive analytics Sebastian Raschka Packt Publishing Limited, Packt Publishing, Birmingham, UK, 2015

Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics About This Book <ul> <li>Leverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualization </li> <li>Learn effective strategies and best practices to improve and optimize machine learning systems and algorithms </li> <li>Ask – and answer – tough questions of your data with robust statistical models, built for a range of datasets </li></ul>Who This Book Is For If you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource. What You Will Learn <ul> <li>Explore how to use different machine learning models to ask different questions of your data </li> <li>Learn how to build neural networks using Keras and Theano </li> <li>Find out how to write clean and elegant Python code that will optimize the strength of your algorithms </li> <li>Discover how to embed your machine learning model in a web application for increased accessibility </li> <li>Predict continuous target outcomes using regression analysis </li> <li>Uncover hidden patterns and structures in data with clustering </li> <li>Organize data using effective pre-processing techniques </li> <li>Get to grips with sentiment analysis to delve deeper into textual and social media data </li></ul>In Detail Machine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data – its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success. Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world's leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuring guidance and tips on everything from sentiment analysis to neural networks, you'll soon be able to answer some of the most important questions facing you and your organization. Style and approach Python Machine Learning connects the fundamental theoretical principles behind machine learning to their practical application in a way that focuses you on asking and answering the right questions. It walks you through the key elements of Python and its powerful machine learning libraries, while demonstrating how to get to grips with a range of statistical models.

English [en] · EPUB · 15.6MB · 2015 · 📘 Book (non-fiction) · 🚀/lgli/lgrs/nexusstc/upload/zlib · Save

upload/trantor/en/Mirjalili, Vahid/Python Machine Learning ú 2nd Edition.epub

Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow, 2nd Edition Sebastian Raschka, Vahid Mirjalili Packt Publishing Limited, Expert insight, 2. edition, fully revised and updated, Birmingham ; Mumbai, 2017

Link to the GitHub Repository containing the code examples and additionalmaterial: [ of the most innovative breakthroughs and exciting new technologies can beattributed to applications of machine learning. We are living in an age wheredata comes in abundance, and thanks to the self-learning algorithms from thefield of machine learning, we can turn this data into knowledge. Automatedspeech recognition on our smart phones, web search engines, e-mail spamfilters, the recommendation systems of our favorite movie streaming services –machine learning makes it all possible.Thanks to the many powerful open-source libraries that have been developed inrecent years, machine learning is now right at our fingertips. Python providesthe perfect environment to build machine learning systems productively.This book will teach you the fundamentals of machine learning and how toutilize these in real-world applications using Python. Step-by-step, you willexpand your skill set with the best practices for transforming raw data intouseful information, developing learning algorithms efficiently, and evaluatingresults.You will discover the different problem categories that machine learning cansolve and explore how to classify objects, predict continuous outcomes withregression analysis, and find hidden structures in data via clustering. Youwill build your own machine learning system for sentiment analysis andfinally, learn how to embed your model into a web app to share with the worldwords : 141799

English [en] · EPUB · 28.6MB · 2017 · 📗 Book (unknown) · 🚀/upload/zlib · Save

nexusstc/The Official Raspberry Pi Projects Book/d8322379620245fcd21eccc3855b8c78.pdf

The official Raspberry Pi projects book. Volume 2 The Makers of the Magpi Magazine The MagPi, Volume 2, 2016

If you’re one of those new people, then we heartily welcome you to the latest Raspberry Pi Official Projects Book. With 200 pages of excellent guides, inspiring projects, and informative reviews, it should keep you busy learning about all the amazing things you can do with your Raspberry Pi. We even have a Getting Started guide if you’re trying to figure out where to begin. For Pi veterans, there are some truly challenging builds to get stuck into as well.

English [en] · PDF · 47.3MB · 2016 · 📘 Book (non-fiction) · 🚀/lgli/lgrs/nexusstc/zlib · Save

upload/trantor/en/Raschka, Sebastian/Python_ Real-World Data Science.epub

Python: real-world data science : unleash the power of Python and its robust data science capabilities with your course guide Antika Thakur : a course in four modules Raschka, Sebastian & Layton, Robert & Czygan, Martin & Vo.T.H, Phuong & Romano, Fabrizio & Phillips, Dusty Packt Publishing Limited, Packt Publishing, Birmingham, UK, 2015

Link to the GitHub Repository containing the code examples and additionalmaterial: [ of the most innovative breakthroughs and exciting new technologies can beattributed to applications of machine learning. We are living in an age wheredata comes in abundance, and thanks to the self-learning algorithms from thefield of machine learning, we can turn this data into knowledge. Automatedspeech recognition on our smart phones, web search engines, e-mail spamfilters, the recommendation systems of our favorite movie streaming services –machine learning makes it all possible.Thanks to the many powerful open-source libraries that have been developed inrecent years, machine learning is now right at our fingertips. Python providesthe perfect environment to build machine learning systems productively.This book will teach you the fundamentals of machine learning and how toutilize these in real-world applications using Python. Step-by-step, you willexpand your skill set with the best practices for transforming raw data intouseful information, developing learning algorithms efficiently, and evaluatingresults.You will discover the different problem categories that machine learning cansolve and explore how to classify objects, predict continuous outcomes withregression analysis, and find hidden structures in data via clustering. Youwill build your own machine learning system for sentiment analysis andfinally, learn how to embed your model into a web app to share with the worldwords : 302285

English [en] · EPUB · 57.6MB · 2015 · 📘 Book (non-fiction) · 🚀/upload/zlib · Save

lgli/Sebastian Raschka - Python Machine Learning (Packt).pdf

Learning scikit-learn : machine learning in Python : experience the benefits of machine learning techniques by applying them to real-world problems using Python and the open source scikit-learn library Sebastian Raschka Packt Publishing - ebooks Account, Packt Publishing, Birmingham, England, 2015

Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analyticsKey FeaturesLeverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualizationLearn effective strategies and best practices to improve and optimize machine learning systems and algorithmsAsk – and answer – tough questions of your data with robust statistical models, built for a range of datasetsBook DescriptionMachine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data – its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success. Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world's leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuring guidance and tips on everything from sentiment analysis to neural networks, you'll soon be able to answer some of the most important questions facing you and your organization. What you will learnExplore how to use different machine learning models to ask different questions of your dataLearn how to build neural networks using Keras and TheanoFind out how to write clean and elegant Python code that will optimize the strength of your algorithmsDiscover how to embed your machine learning model in a web application for increased accessibilityPredict continuous target outcomes using regression analysisUncover hidden patterns and structures in data with clusteringOrganize data using effective pre-processing techniquesGet to grips with sentiment analysis to delve deeper into textual and social media dataWho this book is forIf you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource.

English [en] · PDF · 10.4MB · 2015 · 📘 Book (non-fiction) · 🚀/lgli/zlib · Save

lgli/F:\!upload\_books\Machine Learning for OpenCV.epub

Machine learning for OpenCV : advanced methods and deep learning Michael Beyeler Packt Publishing Limited, Бестселлеры O'Reilly, Санкт-Петербург [и др.], Russia, 2018

"A practical introduction to the world of machine learning and image processing using OpenCV and Python. Computer vision is one of today's most exciting application fields of Machine Learning, From self-driving cars to medical diagnosis, computer vision has been widely used in various domains. This course will cover essential concepts such as classifiers and clustering and will also help you get acquainted with neural networks and Deep Learning to address real-world problems. The course will also guide you through creating custom graphs and visualizations, and show you how to go from raw data to beautiful visualizations. By the end of this course, you will be ready to create your own ML system and will also be able to take on your own machine learning problems."--Resource description page. Read more... Abstract: "A practical introduction to the world of machine learning and image processing using OpenCV and Python. Computer vision is one of today's most exciting application fields of Machine Learning, From self-driving cars to medical diagnosis, computer vision has been widely used in various domains. This course will cover essential concepts such as classifiers and clustering and will also help you get acquainted with neural networks and Deep Learning to address real-world problems. The course will also guide you through creating custom graphs and visualizations, and show you how to go from raw data to beautiful visualizations. By the end of this course, you will be ready to create your own ML system and will also be able to take on your own machine learning problems."--Resource description page

English [en] · EPUB · 28.0MB · 2018 · 📘 Book (non-fiction) · 🚀/lgli/lgrs/nexusstc/zlib · Save

nexusstc/Python и машинное обучение/5eaf0737ed44068d8f7d8f896d4579b7.pdf

Python и машинное обучение: наука и искусство построения алгоритмов, которые извлекают знания из данных Себастьян Рашка; перевод с англ. А. В. Логунова ДМК Пресс, Цветное издание, Москва, Russia, 2017

Машинное обучение и прогнозная аналитика преобразуют традиционную схему функционирования предприятий и других организаций. Эта книга предоставит вам доступ в мир прогнозной аналитики и продемонстрирует, почему Python является одним из ведущих языков науки о данных. Если вы хотите глубже и точнее анализировать данные либо нуждаетесь в усовершенствовании и расширении систем машинного обучения, эта книга окажет вам неоценимую помощь. Ознакомившись с широким кругом мощных программных библиотек Python, в том числе scikit-learn, Theano и Keras, а также получив советы по всем вопросам начиная с анализа мнений и заканчивая нейронными сетями, вы сможете принять важные решения, во многом определяющие деятельность вашей организации. Чему вы научитесь, прочитав эту книгу: • исследовать, как используются разные машинно-обучаемые модели, которые формулируют те или иные вопросы в отношении данных; • конструировать нейронные сети при помощи библиотек Theano и Keras; • писать красивый и лаконичный программный код на Python с оптимальным использованием созданных вами алгоритмов; • встраивать вашу машинно-обучаемую модель в веб-приложение для повышения ее общедоступности; • предсказывать непрерывнозначные результаты при помощи регрессионного анализа; • обнаруживать скрытые повторяющиеся образы и структуры в данных посредством кластерного анализа; • организовывать данные с помощью эффективных методов предобработки и использовать передовые практические подходы к оценке машиннообучаемых моделей; • осуществлять анализ мнений, позволяющий подробнее интерпретировать текстовые данные и информацию из социальных сетей. Если вы хотите узнать, как использовать Python, чтобы начать отвечать на критические вопросы в отношении ваших данных, возьмите данную книгу — и неважно, хотите ли вы приступить к изучению науки о данных с нуля или же намереваетесь расширить о ней свои знания, это принципиальный ресурс, который нельзя упускать. Крайне необходимое издание по новейшей предсказательной аналитике для более глубокого понимания методологии машинного обучения!

Russian [ru] · PDF · 157.1MB · 2017 · 📘 Book (non-fiction) · 🚀/lgli/lgrs/nexusstc/zlib · Save

lgli/Рашка С - Python и машинное обучение (2017, ДМК Пресс).pdf

Python и машинное обучение: наука и искусство построения алгоритмов, которые извлекают знания из данных Себастьян Рашка; перевод с англ. А. В. Логунова ДМК Пресс, Цветное издание, Москва, Russia, 2017

Книга предоставит вам доступ в мир прогнозной аналитики и продемонстрирует , почем у Python является одним из лидирующих языков науки о данных. Охватывая широкийкруг мощных библиотек Python, в том числе scikit-learn, Theano и Keras, предлаrая руководство и советы по всем вопросам, начиная с анализа мнений и заканчивая нейроннымисетями, книга ответит на большинство ваших вопросов по машинному обучению.Издание предназначено для специалистов по анализу данных, находящихся в поискахболее широкого и практического понимания принципов машинного обучения.

Russian [ru] · PDF · 157.0MB · 2017 · 📘 Book (non-fiction) · 🚀/lgli/zlib · Save