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Amazon Top 20 Books in Neural Networks


These are the most popular neural networks books on Amazon. Perhaps there is something of interest to you here.



By Matthew Mayo.

The recent explosion of interest in data science and data mining, along with the renewed interest in neural networks and deep learning, has been mirrored by an explosion in book titles on these same topics. One of the best ways to decide which books could be useful for your career is to look at which books others are reading.

This post details the 20 most popular titles in Amazon's Neural Networks Books category as of Nov 30, 2015.

Note: KDnuggets gets absolutely no royalties from Amazon - this list is presented only to help our readers evaluate interesting books.

Top Amazon Books Neural Networks

1. Python Machine Learning
by Sebastian Raschka
4.9 out of 5 stars (12 reviews)
Paperback, $40.49

2. Learning From Data
by Yaser S. Abu-Mostafa, Malik Magdon-Ismail, Hsuan-Tien Lin
4.6 out of 5 stars (95 reviews)
Hardcover, from $28.00

3. Python Machine Learning
by Sebastian Raschka
4.9 out of 5 stars (12 reviews)
Kindle, $26.92

4. Artificial Intelligence for Humans, Volume 3: Deep Learning and Neural Networks
by Jeff Heaton
No ratings or reviews
Kindle, $7.47

5. Introduction to the Math of Neural Networks
by Jeff Heaton
4.0 out of 5 stars (25 reviews)
Kindle, $7.69

6. Artificial Intelligence for Humans, Volume 3: Deep Learning and Neural Networks
by Jeff Heaton
No ratings or reviews
Paperback, $22.49

7. Neural Network Design
by Martin T. Hagan, Howard B. Demuth, Mark Beale
4.5 out of 5 stars (12 reviews)
Hardcover, from $0.58

8. Deep Belief Nets in C++ and CUDA C: Volume 1: Restricted Boltzmann Machines and Supervised Feedforward Networks
by Timothy Masters
4.7 out of 5 stars (3 reviews)
Paperback, $44.96

9. Smart Machines: IBM's Watson and the Era of Cognitive Computing
by John E. Kelly III, Steve Hamm
3.9 out of 5 stars (45 reviews)
Hardcover, $18.07

10. Not Applicable (that book was not actually relevant to Neural Networks).

11. Code Your Own Neural Network: A step-by-step explanation
by Steven C. Shaffer
3.8 out of 5 stars (9 reviews)
Kindle, $3.83

12. Not applicable.

13. Intelligence Emerging: Adaptivity and Search in Evolving Neural Systems
by Keith L. Downing
No ratings or reviews
Hardcover, $47.50

14. Collective Intelligence in Action
by Satnam Alag
4.4 out of 5 stars (21 reviews)
Paperback, $31.73

15. Deep Belief Nets in C++ and CUDA C: Volume II: Autoencoding in the Complex Domain (Volume 2)
by Timothy Masters
4.0 out of 5 stars (3 reviews)
Paperback, $42.35

16. An Introduction to Neural Networks
by Kevin Gurney
4.7 out of 5 stars (7 reviews)
Paperback, from $2.96

17. Learning Deep Architectures for AI
by Yoshua Bengio
3.0 out of 5 stars (3 reviews)
Paperback, $90.00

18. Neural Networks for Pattern Recognition
by Christopher M. Bishop
4.6 out of 5 stars (27 reviews)
Paperback, $96.11

19. Intelligent Control Systems Using Soft Computing Methodologies
by Ali Zilouchian, Mo Jamshidi (Editors)
No ratings and reviews
Hardcover, $132.95

20. Neural Network Design
by Martin T. Hagan, Howard B. Demuth, Mark H. Beale, Orlando De Jesús
5.0 out of 5 stars (3 reviews)
Paperback, $26.26

21. Information Theory, Inference, and Learning Algorithms
by David J. C. MacKay
4.3 out of 5 stars (24 reviews)
Paperback, $76.76

22. Machine Learning
by Tom M. Mitchell
4.2 out of 5 stars (56 reviews)
Hardcover, $218.80

Bio: Matthew Mayo is a computer science graduate student currently working on his thesis parallelizing machine learning algorithms. He is also a student of data mining, a data enthusiast, and an aspiring machine learning scientist.

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