Practical Deep Learning: A Python-Based Introduction


Practical Deep Learning: A Python-Based Introduction
Authors: Ron Kneusel
Year: 2021
Publisher: No Starch Press
Language: English
ISBN 13: 9781718500747
ISBN 10: 1718500742
Categories: Computers, Computer Science
Pages: 320 / 319
Edition: 1

Availability: 5000 in stock

SKU: 9781718500747 Categories: ,

Practical Deep Learning: A Python-Based Introduction Ron Kneusel
Practical Deep Learning teaches total beginners how to build the datasets and models needed to train neural networks for your own DL projects.
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.  
The perfect introduction to this dynamic, ever-expanding field, Practical Deep Learning will give you the skills and confidence to dive into your own machine learning projects.
Author Bio Ronald T. Kneusel earned a PhD in machine learning from the University of Colorado, Boulder, has nearly 20 years of machine learning experience in industry, and is presently pursuing deep-learning projects with L3Harris Technologies, Inc. Kneusel is also the author of Numbers and Computers (2nd ed., Springer 2017) and Random Numbers and Computers (Springer 2018).
Computers – Computer Science
No Starch Press
ISBN 10:
ISBN 13:
166 MB


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Practical Deep Learning: A Python-Based Introduction

Availability: 5000 in stock