No Starch Press | Practical Deep Learning: A Python-Based Introduction (2021 EN)

Author: Ronald T. Kneusel
Full Title: Practical Deep Learning: A Python-Based Introduction
Publisher: No Starch Press (March 16, 2021)
Year: 2021
ISBN-13: 9781718500754 (978-1-7185-0075-4), 9781718500747 (978-1-7185-0074-7)
ISBN-10: 1718500750, 1718500742
Pages: 464
Language: English
Genre: Educational: Deep Learning
File type: EPUB (True), Code Files
Quality: 10/10
Price: $59.95


If you’ve been curious about machine learning but didn’t know where to start, this is the book you’ve been waiting for. Focusing on the subfield of machine learning known as deep learning, it explains core concepts and gives you the foundation you need to start building your own models. Rather than simply outlining recipes for using existing toolkits, Practical Deep Learning teaches you the why of deep learning and will inspire you to explore further.

All you need is basic familiarity with computer programming and high school math—the book will cover the rest. After an introduction to Python, you’ll move through key topics like how to build a good training dataset, work with the scikit-learn and Keras libraries, and evaluate your models’ performance.


You’ll also learn:
✓ How to use classic machine learning models like k-Nearest Neighbors, Random Forests, and Support Vector Machines
✓ How neural networks work and how they’re trained
✓ How to use convolutional neural networks
✓ How to develop a successful deep learning model from scratch

You’ll conduct experiments along the way, building to a final case study that incorporates everything you’ve learned.

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