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Python Machine Learning eBook (Third Edition) Worth $32 Available for Free

Python Machine Learning Third Edition Box Shot

Python Machine Learning Third Edition is the definitive resource for learning machine learning and deep learning with Python. It can serve as both a detailed guide and a handy reference while you construct your machine learning systems.

They usually sell this book by Sebastian Raschka and Vahid Mirjalili on Amazon for $31.49 (Kindle version) or $46.79 (paperback version).

For a limited time, anyone who signs up for Packt’s newsletter can get a free ebook version (PDF).

To grab this free ebook, visit this .

Enter your first and last name, and email address, and check the box to agree to Packt’s terms and conditions.

Click “Submit and Request Ebook”.

Wait for a few minutes and check your email inbox. ( will send you an email.

Open the email and click “Redeem Now” to download the ebook.

Note: You can only use this link three times.

The ebook (PDF file) will have your email address and a unique code generated for your email address watermarked on it.

About Python Machine Learning-3rd Edition:

You probably know that machine learning has become one of the most exciting technologies of our time. You may have heard about it in the news or on social media. Big companies like Google, Facebook, Apple, Amazon, and IBM put a lot of money into research and applications for machine learning.

This exciting field opens up new possibilities and is now an important part of our everyday lives. Consider the voice assistant on our smartphones, customer recommendations, the prevention of credit card fraud, the elimination of spam from our inboxes, the early detection and diagnosis of medical conditions, and so on.

This book is for you if you know Python and are interested in applying it to machine learning and deep learning. If you don’t know anything about machine learning or want to learn more, this is the best place to start. This book is perfect for anyone who wants to teach computers how to learn from data. It was written for developers and data scientists who want to write a practical code for machine learning and deep learning.

The book goes into detail about all the most important machine-learning techniques. It has simple explanations, visuals, and working examples.

In this machine learning book, Raschka and Mirjalili don’t just tell you what to do. Instead, they teach you the basic ideas behind machine learning, so you can make your own models and apps.

They update this new third edition for TensorFlow 2.0. It shows readers how to use the new Keras API and the latest additions to scikit-learn. They have also expanded it to include a look at GANs and cutting-edge reinforcement learning techniques based on deep learning. Last but not least, this book also looks at sentiment analysis, which is a part of natural language processing (NLP). This will help you learn how to use machine learning algorithms to put documents into groups.

This book is a guide to using Python for machine learning. You can use it if you are a Python developer who is new to machine learning or if you want to know more about the latest developments.

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