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Deep Learning Andrew Glassner

Deep Learning By Andrew Glassner

Deep Learning by Andrew Glassner

Reviews:
$97.29
Condition - New
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Summary

An accessible, highly-illustrated introduction to deep learning that offers visual and conceptual explanations instead of equations. Readers learn how to use key deep learning algorithms without the need for complex math.

Deep Learning Summary

Deep Learning: A Visual Approach by Andrew Glassner

Deep Learning: A Visual Approach helps demystify the algorithms that enable computers to drive cars, win chess tournaments, and create symphonies, while giving readers the tools necessary to build their own systems to help them find the information hiding within their own data, create 'deep dream' artwork, or create new stories in the style of their favorite authors.

Deep Learning Reviews

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 , @nabeelhasan25

This is the best technical book I've ever read. I'm essentially speechless. Thank you, @AndrewGlassner!
-Maciej Chmielarz, @MaciejChmielarz, Software Developer

About 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.

Table of Contents

Part I: Foundational Ideas
1. An Overview of Machine Learning Techniques
2. Essential Statistical Ideas
3. Probability
4. Bayes' Rule
5. Curves and Surfaces
6. Information Theory
Part II: Basic Machine Learning
7. Classification
8. Training and Testing
9. Overfitting and Underfitting
10. Data Preparation
11. Classifiers
12. Ensembles
Part III: Deep Learning Basics
13. Neural Networks
14. Backpropagation
15. Optimizers
Part IV: Beyond the Basics
16. Convolutional Neural Networks
17. Convnets in Practice
18. Recurrent Neural Networks
19. Autoencoders
20. Reinforcement Learning
21. Generative Adversarial Networks
22. Creative Applications
Index

Additional information

NGR9781718500723
9781718500723
1718500726
Deep Learning: A Visual Approach by Andrew Glassner
Andrew Glassner
New
Hardback
No Starch Press,US
2021-06-29
1200
N/A
Book picture is for illustrative purposes only, actual binding, cover or edition may vary.
This is a new book - be the first to read this copy. With untouched pages and a perfect binding, your brand new copy is ready to be opened for the first time

Customer Reviews - Deep Learning