9 Best Neural Networks Books
Goal: Find the best Neural Networks books according to the internet (not just one person's opinion).
Method:
- Search for "best neural networks books" and study the top 5+ pages.
- Add only the books mentioned 2+ times.
- Rank the results neatly here.
9 Best Neural Networks Books
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Deep Learning
by Ian Goodfellow
Also recommended by:
Neural Networks for Pattern Recognition
by Christopher M. Bishop
Deep Learning with Python
by Francois Chollet
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow
Concepts, Tools, and Techniques to Build Intelligent Systems
by Aurélien Géron
Deep Learning
A Practitioner's Approach
by Josh Patterson
Hands-On Deep Learning Algorithms with Python
Master Deep Learning Algorithms with Extensive Math by Implementing Them Using TensorFlow
by Sudharsan Ravichandiran
Neural Networks and Deep Learning
A Textbook
by Charu C. Aggarwal
Neural Smithing
Supervised Learning in Feedforward Artificial Neural Networks
by Russell Reed
TensorFlow 1.x Deep Learning Cookbook
Over 90 Unique Recipes To Solve Artificial-Intelligence Driven Problems With Python
by Antonio Gulli
Sources
- 1
3 Must-Own Books for Deep Learning Practitioners - MachineLearningMastery.com
machinelearningmastery.com
- 2
The 7 best deep learning books you should be reading right now - PyImageSearch
pyimagesearch.com
- 3
10 Best Books on Neural Networks and Deep Learning in 2023
mltut.com
- 4
10 Best Deep Learning Books for Beginner & Experts in 2022 [Updated]
hackr.io
- 5
Amazon Top 20 Books in Neural Networks - KDnuggets
kdnuggets.com
Edited by
Software engineer whose passion for tracking book recommendations from podcasts inspired the creation of MRB.
Lead investor at 3one4 Capital whose startup expertise and love for books helped shaped MRB and its growth.
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