Deep Learning
By Andrew Glassner
By Andrew Glassner
By Andrew Glassner
By Andrew Glassner
Category: Science & Technology
Category: Science & Technology
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$99.99
Jun 29, 2021 | ISBN 9781718500723
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Jun 22, 2021 | ISBN 9781718500730
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Praise
“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
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
21 Books You’ve Been Meaning to Read
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