Python Machine Learning - Third Edition (Code Files)

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  • Python Machine Learning - Third Edition (Code Files)
    Python Machine Learning - Third Edition (Code Files)
    by Sebastian Raschka and Vahid Mirjalili
    English | 2019 | ISBN: 1789955750 | - | Code Files (ZIP) | 1.41 MB

Python Machine Learning - Third Edition (Code Files) Python Machine Learning - Third Edition (Code Files) by Sebastian Raschka and Vahid Mirjalili English | 2019 | ISBN: 1789955750 | - | Code Files (ZIP) | 1.41 MB 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. 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 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. If you want to support my blog, then you can buy a premium account through any of my files (i.e. on the download page of my book). In this case, I get a percent of sale and can continue to delight you with new books! Buy Premium From My Links To Get Resumable Support,Max Speed & Support Me
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