Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Save more on your purchases! discount-offer-chevron-icon
Savings automatically calculated. No voucher code required.
Arrow left icon
All Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Newsletter Hub
Free Learning
Arrow right icon
timer SALE ENDS IN
0 Days
:
00 Hours
:
00 Minutes
:
00 Seconds
Python Machine Learning
Python Machine Learning

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

Arrow left icon
Profile Icon Sebastian Raschka Profile Icon Vahid Mirjalili
Arrow right icon
$43.99
Full star icon Full star icon Full star icon Full star icon Half star icon 4.4 (42 Ratings)
eBook 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
$43.99
Full star icon Full star icon Full star icon Full star icon Half star icon 4.4 (42 Ratings)
eBook 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

What do you get with eBook?

Product feature icon Instant access to your Digital eBook purchase
Product feature icon Download this book in EPUB and PDF formats
Product feature icon Access this title in our online reader with advanced features
Product feature icon DRM FREE - Read whenever, wherever and however you want
Product feature icon AI Assistant (beta) to help accelerate your learning
OR
Modal Close icon
Payment Processing...
tick Completed

Billing Address

Table of content icon View table of contents Preview book icon Preview Book

Python Machine Learning

Left arrow icon Right arrow icon
Download code icon Download Code

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

Country selected
Publication date, Length, Edition, Language, ISBN-13
Publication date : Dec 12, 2019
Length: 772 pages
Edition : 3rd
Language : English
ISBN-13 : 9781789958294
Vendor :
Google
Category :
Languages :
Tools :

What do you get with eBook?

Product feature icon Instant access to your Digital eBook purchase
Product feature icon Download this book in EPUB and PDF formats
Product feature icon Access this title in our online reader with advanced features
Product feature icon DRM FREE - Read whenever, wherever and however you want
Product feature icon AI Assistant (beta) to help accelerate your learning
OR
Modal Close icon
Payment Processing...
tick Completed

Billing Address

Product Details

Publication date : Dec 12, 2019
Length: 772 pages
Edition : 3rd
Language : English
ISBN-13 : 9781789958294
Vendor :
Google
Category :
Languages :
Tools :

Packt Subscriptions

See our plans and pricing
Modal Close icon
$12.99 billed monthly
Feature tick icon Unlimited access to Packt's library of 6,500+ practical books and videos
Feature tick icon Constantly refreshed with 50+ new titles a month
Feature tick icon Exclusive Early access to books as they're written
Feature tick icon Solve problems while you work with advanced search and reference features
Feature tick icon Offline reading on the mobile app
Feature tick icon Simple pricing, no contract
$129.99 billed annually
Feature tick icon Unlimited access to Packt's library of 6,500+ practical books and videos
Feature tick icon Constantly refreshed with 50+ new titles a month
Feature tick icon Exclusive Early access to books as they're written
Feature tick icon Solve problems while you work with advanced search and reference features
Feature tick icon Offline reading on the mobile app
Feature tick icon Choose a DRM-free eBook or Video every month to keep
Feature tick icon PLUS own as many other DRM-free eBooks or Videos as you like for just $5 each
Feature tick icon Exclusive print discounts
$179.99 billed in 18 months
Feature tick icon Unlimited access to Packt's library of 6,500+ practical books and videos
Feature tick icon Constantly refreshed with 50+ new titles a month
Feature tick icon Exclusive Early access to books as they're written
Feature tick icon Solve problems while you work with advanced search and reference features
Feature tick icon Offline reading on the mobile app
Feature tick icon Choose a DRM-free eBook or Video every month to keep
Feature tick icon PLUS own as many other DRM-free eBooks or Videos as you like for just $5 each
Feature tick icon Exclusive print discounts

Frequently bought together


Stars icon
Total $ 161.97
Machine Learning for Algorithmic Trading
$57.99
Python Machine Learning
$54.99
Advanced Deep Learning with Python
$48.99
Total $ 161.97 Stars icon
Visually different images

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%
Filter icon Filter
Top Reviews

Filter reviews by




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
Get free access to Packt library with over 7500+ books and video courses for 7 days!
Start Free Trial

FAQs

How do I buy and download an eBook? Chevron down icon Chevron up icon

Where there is an eBook version of a title available, you can buy it from the book details for that title. Add either the standalone eBook or the eBook and print book bundle to your shopping cart. Your eBook will show in your cart as a product on its own. After completing checkout and payment in the normal way, you will receive your receipt on the screen containing a link to a personalised PDF download file. This link will remain active for 30 days. You can download backup copies of the file by logging in to your account at any time.

If you already have Adobe reader installed, then clicking on the link will download and open the PDF file directly. If you don't, then save the PDF file on your machine and download the Reader to view it.

Please Note: Packt eBooks are non-returnable and non-refundable.

Packt eBook and Licensing When you buy an eBook from Packt Publishing, completing your purchase means you accept the terms of our licence agreement. Please read the full text of the agreement. In it we have tried to balance the need for the ebook to be usable for you the reader with our needs to protect the rights of us as Publishers and of our authors. In summary, the agreement says:

  • You may make copies of your eBook for your own use onto any machine
  • You may not pass copies of the eBook on to anyone else
How can I make a purchase on your website? Chevron down icon Chevron up icon

If you want to purchase a video course, eBook or Bundle (Print+eBook) please follow below steps:

  1. Register on our website using your email address and the password.
  2. Search for the title by name or ISBN using the search option.
  3. Select the title you want to purchase.
  4. Choose the format you wish to purchase the title in; if you order the Print Book, you get a free eBook copy of the same title. 
  5. Proceed with the checkout process (payment to be made using Credit Card, Debit Cart, or PayPal)
Where can I access support around an eBook? Chevron down icon Chevron up icon
  • If you experience a problem with using or installing Adobe Reader, the contact Adobe directly.
  • To view the errata for the book, see www.packtpub.com/support and view the pages for the title you have.
  • To view your account details or to download a new copy of the book go to www.packtpub.com/account
  • To contact us directly if a problem is not resolved, use www.packtpub.com/contact-us
What eBook formats do Packt support? Chevron down icon Chevron up icon

Our eBooks are currently available in a variety of formats such as PDF and ePubs. In the future, this may well change with trends and development in technology, but please note that our PDFs are not Adobe eBook Reader format, which has greater restrictions on security.

You will need to use Adobe Reader v9 or later in order to read Packt's PDF eBooks.

What are the benefits of eBooks? Chevron down icon Chevron up icon
  • You can get the information you need immediately
  • You can easily take them with you on a laptop
  • You can download them an unlimited number of times
  • You can print them out
  • They are copy-paste enabled
  • They are searchable
  • There is no password protection
  • They are lower price than print
  • They save resources and space
What is an eBook? Chevron down icon Chevron up icon

Packt eBooks are a complete electronic version of the print edition, available in PDF and ePub formats. Every piece of content down to the page numbering is the same. Because we save the costs of printing and shipping the book to you, we are able to offer eBooks at a lower cost than print editions.

When you have purchased an eBook, simply login to your account and click on the link in Your Download Area. We recommend you saving the file to your hard drive before opening it.

For optimal viewing of our eBooks, we recommend you download and install the free Adobe Reader version 9.