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Python Machine Learning
Python Machine Learning

Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2 , Third Edition

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Profile Icon Sebastian Raschka Profile Icon Vahid Mirjalili
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$12.99 per month
Full star icon Full star icon Full star icon Full star icon Half star icon 4.4 (42 Ratings)
Paperback Dec 2019 772 pages 3rd Edition
eBook
$43.99
Paperback
$54.99
Subscription
Free Trial
Renews at $12.99p/m
Arrow left icon
Profile Icon Sebastian Raschka Profile Icon Vahid Mirjalili
Arrow right icon
$12.99 per month
Full star icon Full star icon Full star icon Full star icon Half star icon 4.4 (42 Ratings)
Paperback Dec 2019 772 pages 3rd Edition
eBook
$43.99
Paperback
$54.99
Subscription
Free Trial
Renews at $12.99p/m
eBook
$43.99
Paperback
$54.99
Subscription
Free Trial
Renews at $12.99p/m

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Python Machine Learning

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Key benefits

  • Third edition of the bestselling, widely acclaimed Python machine learning book
  • Clear and intuitive explanations take you deep into the theory and practice of Python machine learning
  • Fully updated and expanded to cover TensorFlow 2, Generative Adversarial Network models, reinforcement learning, and best practices

Description

Python Machine Learning, Third Edition is a comprehensive guide to machine learning and deep learning with Python. It acts as both a step-by-step tutorial, and a reference you'll keep coming back to as you build your machine learning systems. Packed with clear explanations, visualizations, and working examples, the book covers all the essential machine learning techniques in depth. While some books teach you only to follow instructions, with this machine learning book, Raschka and Mirjalili teach the principles behind machine learning, allowing you to build models and applications for yourself. Updated for TensorFlow 2.0, this new third edition introduces readers to its new Keras API features, as well as the latest additions to scikit-learn. It's also expanded to cover cutting-edge reinforcement learning techniques based on deep learning, as well as an introduction to GANs. Finally, this book also explores a subfield of natural language processing (NLP) called sentiment analysis, helping you learn how to use machine learning algorithms to classify documents. This book is your companion to machine learning with Python, whether you're a Python developer new to machine learning or want to deepen your knowledge of the latest developments.

Who is this book for?

If you know some Python and you want to use machine learning and deep learning, pick up this book. Whether you want to start from scratch or extend your machine learning knowledge, this is an essential resource. Written for developers and data scientists who want to create practical machine learning and deep learning code, this book is ideal for anyone who wants to teach computers how to learn from data.

What you will learn

  • Master the frameworks, models, and techniques that enable machines to learn from data
  • Use scikit-learn for machine learning and TensorFlow for deep learning
  • Apply machine learning to image classification, sentiment analysis, intelligent web applications, and more
  • Build and train neural networks, GANs, and other models
  • Discover best practices for evaluating and tuning models
  • Predict continuous target outcomes using regression analysis
  • Dig deeper into textual and social media data using sentiment analysis

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Dec 12, 2019
Length: 772 pages
Edition : 3rd
Language : English
ISBN-13 : 9781789955750
Vendor :
Google
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Product Details

Publication date : Dec 12, 2019
Length: 772 pages
Edition : 3rd
Language : English
ISBN-13 : 9781789955750
Vendor :
Google
Category :
Languages :
Concepts :
Tools :

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Table of Contents

20 Chapters
Giving Computers the Ability to Learn from Data Chevron down icon Chevron up icon
Training Simple Machine Learning Algorithms for Classification Chevron down icon Chevron up icon
A Tour of Machine Learning Classifiers Using scikit-learn Chevron down icon Chevron up icon
Building Good Training Datasets – Data Preprocessing Chevron down icon Chevron up icon
Compressing Data via Dimensionality Reduction Chevron down icon Chevron up icon
Learning Best Practices for Model Evaluation and Hyperparameter Tuning Chevron down icon Chevron up icon
Combining Different Models for Ensemble Learning Chevron down icon Chevron up icon
Applying Machine Learning to Sentiment Analysis Chevron down icon Chevron up icon
Embedding a Machine Learning Model into a Web Application Chevron down icon Chevron up icon
Predicting Continuous Target Variables with Regression Analysis Chevron down icon Chevron up icon
Working with Unlabeled Data – Clustering Analysis Chevron down icon Chevron up icon
Implementing a Multilayer Artificial Neural Network from Scratch Chevron down icon Chevron up icon
Parallelizing Neural Network Training with TensorFlow Chevron down icon Chevron up icon
Going Deeper – The Mechanics of TensorFlow Chevron down icon Chevron up icon
Classifying Images with Deep Convolutional Neural Networks Chevron down icon Chevron up icon
Modeling Sequential Data Using Recurrent Neural Networks Chevron down icon Chevron up icon
Generative Adversarial Networks for Synthesizing New Data Chevron down icon Chevron up icon
Reinforcement Learning for Decision Making in Complex Environments Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon
Index Chevron down icon Chevron up icon

Customer reviews

Top Reviews
Rating distribution
Full star icon Full star icon Full star icon Full star icon Half star icon 4.4
(42 Ratings)
5 star 66.7%
4 star 19%
3 star 4.8%
2 star 4.8%
1 star 2.4%
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Top Reviews

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THEODOROS ZAFEIRIDIS Jul 16, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
the best among many others
Feefo Verified review Feefo
Amazon Customer Feb 19, 2020
Full star icon Full star icon Full star icon Full star icon Full star icon 5
A clearly explained theory and detailed python implementation
Amazon Verified review Amazon
Puneet Apr 29, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Easy language book...
Amazon Verified review Amazon
Tony Jun 20, 2020
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I have not finished this book and I just reached chapter 16, but here are my key takeaways for this book:1. Everything before chapter 13, before the book fully gets into deep learning and TensorFlow, are great. With already some background in python for data analysis (I have also taken the Andrew Ng's Coursera course on Machine Learning), this book supplements my knowledge greatly. The biggest highlight I would say is that it introduces you JUST ENOUGH concepts for you to understand how everything works. In addition, the contents are structured really well, too. If I were to rate this section of the book, I would give 10/10 although it would be better to have some exercises, you can always practice using Kaggle datasets.2. Since chapter 13 when the book gets into deep learning, things get worse a little bit... The contents are still good in general, however the connections between contents might not be the case. The connections between contents are important for new learners because that helps them to understand how A leads to B and then leads to C. Here, I found the actual TensorFlow documentation a really good material to review along with the book. After reviewing those documentations, coming back to this book allows me to comprehend much more than reading the first time. In addition, if you are not careful enough, the deep learning sections also seems to have accuracy issues with its contents that could confuse people. Even though I have not finished the book, I would give 9/10 for everything I have read for deep learning.
Amazon Verified review Amazon
Cliente Amazon Feb 07, 2022
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Nice and easy intro/hands on for those who know ML and a bit of Python
Amazon Verified review Amazon
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