A Great Collection of Deep Learning (e)Books

• Deep Dive into Different Types of Convolutions for Deep Learning [Theory-based from beginner to advanced level, contains many ideas, Great for Computer Vision, NLP, Speech processing engineers/researchers/students & also appropriate for data scientists]

• Programming PyTorch for Deep Learning - by Ian Pointer [General, Excellent book, based on PyTorch, Programming + Little theory, O’Reilly Publisher]
• AI and Machine Learning for Coders [General, Excellent book, based on TensorFlow, Programming + Little theory, O’Reilly Publisher]
• Deep Learning with PyTorch [General, Good, based on PyTorch, Programming + Little theory, Manning Publisher]
• Deep Learning with Python by Francois Chollet - 2nd edition [General, Good, based on Keras, Programming + Little theory, Manning Publisher]
• Dive into Deep Learning [General, Good, based on Mxnet/PyTorch/TensorFlow/NumPy, Programming + theory, Free (support from Amazon)]
• Deep Learning for Coders With Fastai and Pytorch AI Applications Without a Phd [General, Semi Good, based on PyTorch, Programming + Little theory, O’Reilly Publisher]
• Deep Learning for Coders With Fastai and Pytorch AI Applications Without a Phd - GitHub
• Grokking Deep Learning [General, Semi-Good, Theory in simple language + Programming, Manning Publisher]

• Deep Learning Book, by Shelly Sheynin [Good]
• Understanding Deep Learning

• Deep Learning for Vision Systems - by Elgendy [Computer Vision, Good, based on Keras, Programming + theory, Manning Publisher]

• Practical Natural Language Processing [NLP, Good, Programming + theory, O’Reilly Publisher]
• Natural Language Processing with PyTorch [NLP, Good, Programming + theory, O’Reilly Publisher]
• Natural Language Processing with Transformers [Great]

• Reinforcement Learning, An Introduction [by Richard S. Sutton, MIT Press]
• Deep Reinforcement Learning in Action [by Alexander Zai and Brandon Brown, Good, Programming + Theory, Manning Publisher]
• Deep Learning and the Game of Go [by Max Pumperla and Kevin Ferguson, Good, Programming + Theory, Manning Publisher]
• Grokking Deep Reinforcement Learning [by Miguel Morales, Good, Theory + Programming, Manning Publisher]

• TinyML - Machine Learning with TensorFlow Lite on Arduino and Ultra-Low-Power Microcontrollers -- by Pete Warden & Daniel Situnayake [Good book, based on TensorFlow Lite on Arduino, Programming/Practical, O’Reilly Publisher]
• Practical Deep Learning for Cloud, Mobile, and Edge [Good book, based on Keras/TensorFlow, Programming/Practical, O’Reilly Publisher]
• AI and Machine Learning On-Device Development [Good book, based on ML Kit/TensorFlow Lite/Core ML, Programming/Practical, O’Reilly Publisher]

• Generative Deep Learning - by David Foster [General (i.e., GAN for image/audio/text data), Great book, based on Keras, theory + Programming , O’Reilly Publisher]
• GANs in Action - by Jakub Langr, and Vladimir Bok [Image based, Good, based on Keras, theory + Programming, Manning Publisher]

• Deep Learning with JavaScript: Neural networks in TensorFlow.js [Good, based on JS, Programming + theory, Manning Publisher]
• Hands-on Machine Learning with JavaScript [Programming + Little theory, packtpub]

• Kubeflow for Machine Learning [Great book, O’Reilly Publisher]
• Ansible for DevOps - Server and configuration management for humans
• Ansible for Kubernetes - Automate app deployment on any scale with Ansible and K8s
• Cloud Native DevOps with Kubernetes [Good book, O’Reilly Publisher]
• Kubernetes: Up and Running, 2nd Edition

• Linux Pocket Guide, 3rd Edition, O’Reilly Publisher [Great]

• INSPIRED: How to Create Tech Products Customers Love - 2nd Edition [Great book, Wiley Publisher]
• Managing Humans: Biting and Humorous Tales of a Software Engineering Manager
• The Hard Thing About Hard Things: Building a Business When There Are No Easy Answers
• Cracking the PM Interview
• Building Machine Learning Powered Applications
• People + AI Guidebook (Google Book) [Interesting]

• Python for Data Analysis, 2nd Edition
• Data Science from Scratch, 2nd Edition
• Hands-On Exploratory Data Analysis with Python

• Mining the Social Web, 3rd Edition
• Web Scraping with Python, 2nd Edition
• Practical Web Scraping for Data Science, Apress Publisher

• Python Tricks: The Book [Intermediate & Advanced Level, & Great]
• Python 101
• Python Crash Course, 2nd Edition
• Daily Coding Problem [Great]
• Cracking the Coding Interview
• Cracking the Coding Interview - Solutions

• Practical Statistics for Data Scientists, 2nd Edition
• Naked Statistics
• Bayesian Modeling and Computation in Python

• Artificial Intelligence in Finance [Deep Learning + Finance & Data Science, Good, Programming + theory, O’Reilly Publisher]
• Best Machine Learning Books (Updated for 2020)
• Designing Machine Learning Systems
• Deep Learning Interviews: Hundreds of fully solved job interview questions from a wide range of key topics in AI [Interesting]
• Harvard CS197: AI Research Experiences - The Course Book [Excellent]