Deep Learning
A Visual Approach
$187.84
- Hardcover
768 pages
- Release Date
14 September 2021
Summary
A richly-illustrated, full-color introduction to deep learning that offers visual and conceptual explanations instead of equations. You’ll learn how to use key deep learning algorithms without the need for complex math.
Ever since computers began beating us at chess, they’ve been getting better at a wide range of human activities, from writing songs and generating news articles to helping doctors provide healthcare.
Deep learning is the source of many of these breakthroughs, a…
Book Details
| ISBN-13: | 9781718500723 |
|---|---|
| ISBN-10: | 1718500726 |
| Author: | Andrew Glassner |
| Publisher: | No Starch Press,US |
| Imprint: | No Starch Press,US |
| Format: | Hardcover |
| Number of Pages: | 768 |
| Release Date: | 14 September 2021 |
| Weight: | 1.68kg |
| Dimensions: | 177mm x 234mm |
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Critics Review
“Andrew is famous for his ability to teach complex topics that blend mathematics and algorithms, and this work I think is his best yet.”
—Peter Shirley, Distinguished Research Engineer, Nvidia
“I would recommend that anyone entering this area, or even already familiar with the subject, read it cover-to-cover to firmly ground their understanding.“
—Richard Szeliski, author of Computer Vision: Algorithms and Applications
“This is a comprehensive—yet easy to understand—book about complex concepts and algorithms. Andrew Glassner demonstrates that visualizing concepts as graphs is a tremendous benefit to easy cognition.”
—Thomas Frisendal, author of Graph Data Modeling for NoSQL and SQL
“An absolutely amazing book in the field of Machine Learning. Lots of colored visuals make the concepts very easy to understand.”
—Nabeel حسن, @nabeelhasan25
“This is the best technical book I’ve ever read. I’m essentially speechless. Thank you, @AndrewGlassner!”
—Maciej Chmielarz, @MaciejChmielarz, Software Developer
Andrew Glassner
Andrew Glassner is a research scientist specializing in computer graphics and deep learning. He is currently a Senior Research Scientist at Weta Digital, where he works on integrating deep learning with the production of world-class visual effects for films and television. He has previously worked as a researcher at labs such as the IBM Watson Lab, Xerox PARC, and Microsoft Research. He was Editor in Chief of ACM TOG, the premier research journal in graphics, and Technical Papers Chair for SIGGRAPH, the premier conference in graphics. He’s written or edited a dozen technical books on computer graphics, ranging from the textbook Principles of Digital Image Synthesis to the popular Graphics Gems series, offering practical algorithms for working programmers. Glassner has a PhD in Computer Science from UNC-Chapel Hill.
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