{"id":20081491,"url":"https://github.com/ahkarami/great-deep-learning-books","last_synced_at":"2025-10-04T10:40:32.230Z","repository":{"id":61958785,"uuid":"252831414","full_name":"ahkarami/Great-Deep-Learning-Books","owner":"ahkarami","description":"A Great Collection of Deep Learning (e)Books","archived":false,"fork":false,"pushed_at":"2024-11-23T09:51:00.000Z","size":614,"stargazers_count":135,"open_issues_count":0,"forks_count":30,"subscribers_count":7,"default_branch":"master","last_synced_at":"2025-05-25T10:04:56.865Z","etag":null,"topics":["books","convolutional-neural-networks","deep-learning","deep-neural-networks","ebooks","keras","machine-learning","mxnet","natural-language-processing","pytorch","recurrent-neural-networks","reinforcement-learning","speech-processing","tensorflow"],"latest_commit_sha":null,"homepage":null,"language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/ahkarami.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2020-04-03T20:14:56.000Z","updated_at":"2025-05-23T08:41:41.000Z","dependencies_parsed_at":"2024-11-10T09:22:36.809Z","dependency_job_id":"5e823464-5838-4892-83c6-5ac419542cee","html_url":"https://github.com/ahkarami/Great-Deep-Learning-Books","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/ahkarami/Great-Deep-Learning-Books","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ahkarami%2FGreat-Deep-Learning-Books","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ahkarami%2FGreat-Deep-Learning-Books/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ahkarami%2FGreat-Deep-Learning-Books/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ahkarami%2FGreat-Deep-Learning-Books/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ahkarami","download_url":"https://codeload.github.com/ahkarami/Great-Deep-Learning-Books/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ahkarami%2FGreat-Deep-Learning-Books/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":278302556,"owners_count":25964519,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-10-04T02:00:05.491Z","response_time":63,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["books","convolutional-neural-networks","deep-learning","deep-neural-networks","ebooks","keras","machine-learning","mxnet","natural-language-processing","pytorch","recurrent-neural-networks","reinforcement-learning","speech-processing","tensorflow"],"created_at":"2024-11-13T15:39:17.679Z","updated_at":"2025-10-04T10:40:32.194Z","avatar_url":"https://github.com/ahkarami.png","language":null,"funding_links":[],"categories":[],"sub_categories":[],"readme":"# Great-Deep-Learning-Books\nA Great Collection of Deep Learning (e)Books\n\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"./Books.png?raw=true\" alt=\"All_Books_Image\"/\u003e\n\u003c/p\u003e\n\n## My Book:\n- [**_Deep Dive into Different Types of Convolutions for Deep Learning_**](https://leanpub.com/convolutions-for-deep-learning) [Theory-based from beginner to advanced level, contains many ideas, Great for Computer Vision, NLP, Speech processing engineers/researchers/students \u0026 also appropriate for data scientists]   \n\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"./MyBook_logo2.jpg?raw=true\" alt=\"My_Book_Logo\"/\u003e\n\u003c/p\u003e\n\n\n## Programming based:\n- [Programming PyTorch for Deep Learning - by Ian Pointer](https://www.oreilly.com/library/view/programming-pytorch-for/9781492045342/) [General, **Excellent book**, based on PyTorch, Programming + Little theory, O’Reilly Publisher]  \n- [AI and Machine Learning for Coders](https://www.oreilly.com/library/view/ai-and-machine/9781492078180/) [General, **Excellent book**, based on TensorFlow, Programming + Little theory, O’Reilly Publisher]  \n- [Deep Learning with PyTorch](https://www.manning.com/books/deep-learning-with-pytorch) [General, Good, based on PyTorch, Programming + Little theory, Manning Publisher]    \n- [Deep Learning with Python by Francois Chollet - 2nd edition](https://www.manning.com/books/deep-learning-with-python) [General, Good, based on Keras, Programming + Little theory, Manning Publisher]  \n- [Dive into Deep Learning](http://d2l.ai/) [General, Good, based on Mxnet/PyTorch/TensorFlow/NumPy, Programming + theory, Free (support from Amazon)]  \n- [Deep Learning for Coders With Fastai and Pytorch AI Applications Without a Phd](https://www.oreilly.com/library/view/deep-learning-for/9781492045519/) [General, Semi Good, based on PyTorch, Programming + Little theory, O’Reilly Publisher]   \n- [Deep Learning for Coders With Fastai and Pytorch AI Applications Without a Phd - GitHub](https://github.com/fastai/fastbook)  \n- [Grokking Deep Learning](https://www.manning.com/books/grokking-deep-learning) [General, Semi-Good, Theory in simple language + Programming, Manning Publisher]  \n\n## General Theory-based Books:\n- [Deep Learning Book, by Shelly Sheynin](https://github.com/shellysheynin/Deep-Learning-Book) [Good]    \n- [Understanding Deep Learning](https://udlbook.github.io/udlbook/)  \n\n## Deep Learning \u0026 Computer Vision:\n- [Deep Learning for Vision Systems - by Elgendy](https://www.manning.com/books/deep-learning-for-vision-systems) [Computer Vision, Good, based on Keras, Programming + theory, Manning Publisher]  \n\n## LLMs Books:\n- [3 LLM-based Books](https://www.linkedin.com/posts/udaykamath_if-you-go-to-amazon-you-will-see-these-are-activity-7261047054104195072-I8S7?utm_source=share\u0026utm_medium=member_desktop)  \n\n## Deep Learning \u0026 NLP:\n- [Practical Natural Language Processing](https://www.oreilly.com/library/view/practical-natural-language/9781492054047/) [NLP, Good, Programming + theory, O’Reilly Publisher]  \n- [Natural Language Processing with PyTorch](https://www.oreilly.com/library/view/natural-language-processing/9781491978221/) [NLP, Good, Programming + theory, O’Reilly Publisher]    \n- [Natural Language Processing with Transformers](https://www.oreilly.com/library/view/natural-language-processing/9781098103231/) [**Great**]  \n\n## Reinforcement Learning:\n- [Reinforcement Learning, An Introduction](https://mitpress.mit.edu/books/reinforcement-learning-second-edition) [by Richard S. Sutton, MIT Press]   \n- [Deep Reinforcement Learning in Action](https://www.manning.com/books/deep-reinforcement-learning-in-action) [by Alexander Zai and Brandon Brown, Good, Programming + Theory, Manning Publisher]    \n- [Deep Learning and the Game of Go](https://www.manning.com/books/deep-learning-and-the-game-of-go) [by Max Pumperla and Kevin Ferguson, Good, Programming + Theory, Manning Publisher]   \n- [Grokking Deep Reinforcement Learning](https://www.manning.com/books/grokking-deep-reinforcement-learning) [by Miguel Morales, Good, Theory + Programming, Manning Publisher]  \n\n## TinyML - Deep Learning on Embedded Devices \u0026 Mobile:\n- [TinyML - Machine Learning with TensorFlow Lite on Arduino and Ultra-Low-Power Microcontrollers -- by Pete Warden \u0026 Daniel Situnayake](https://www.oreilly.com/library/view/tinyml/9781492052036/) [Good book, based on TensorFlow Lite on Arduino, Programming/Practical, O’Reilly Publisher]  \n- [Practical Deep Learning for Cloud, Mobile, and Edge](https://www.oreilly.com/library/view/practical-deep-learning/9781492034858/) [Good book, based on Keras/TensorFlow, Programming/Practical, O’Reilly Publisher]  \n- [AI and Machine Learning On-Device Development](https://www.oreilly.com/library/view/ai-and-machine/9781098101732/) [Good book, based on ML Kit/TensorFlow Lite/Core ML, Programming/Practical, O’Reilly Publisher]  \n\n## GANs:\n- [Generative Deep Learning - by David Foster](https://www.oreilly.com/library/view/generative-deep-learning/9781492041931/) [General (_i.e.,_ GAN for image/audio/text data), **Great book**, based on Keras, theory + Programming , O’Reilly Publisher]   \n- [GANs in Action - by Jakub Langr, and Vladimir Bok](https://www.manning.com/books/gans-in-action) [Image based, Good, based on Keras, theory + Programming, Manning Publisher]  \n\n## Machine Learning with JavaScript (ML with JS):\n- [Deep Learning with JavaScript: Neural networks in TensorFlow.js](https://www.manning.com/books/deep-learning-with-javascript) [Good, based on JS, Programming + theory, Manning Publisher]   \n- [Hands-on Machine Learning with JavaScript](https://www.packtpub.com/product/hands-on-machine-learning-with-javascript/9781788998246) [Programming + Little theory, packtpub]  \n\n## Backend for Deep Learning \u0026 Machine Learning:\n- [Kubeflow for Machine Learning](https://www.oreilly.com/library/view/kubeflow-for-machine/9781492050117/) [**Great book**, O’Reilly Publisher]  \n- [Ansible for DevOps - Server and configuration management for humans](https://leanpub.com/ansible-for-devops)  \n- [Ansible for Kubernetes - Automate app deployment on any scale with Ansible and K8s](https://leanpub.com/ansible-for-kubernetes)  \n- [Cloud Native DevOps with Kubernetes](https://www.oreilly.com/library/view/cloud-native-devops/9781492040750/) [**Good book**, O’Reilly Publisher]  \n- [Kubernetes: Up and Running, 2nd Edition](https://www.oreilly.com/library/view/kubernetes-up-and/9781492046523/)\n- [Kubernetes in Action](https://www.manning.com/books/kubernetes-in-action)  \n\n## Linux Learning:\n- [Linux Pocket Guide, 3rd Edition, O’Reilly Publisher](https://www.oreilly.com/library/view/linux-pocket-guide/9781491927557/) [Great]  \n\n## Books about Project Management \u0026 Business Issues:\n- [INSPIRED: How to Create Tech Products Customers Love - 2nd Edition](https://www.wiley.com/en-us/INSPIRED%3A+How+to+Create+Tech+Products+Customers+Love%2C+2nd+Edition-p-9781119387503) [**Great book**, Wiley Publisher]   \n- [Managing Humans: Biting and Humorous Tales of a Software Engineering Manager](https://www.apress.com/gp/book/9781484221570)  \n- [The Hard Thing About Hard Things: Building a Business When There Are No Easy Answers](https://hardthings.bhorowitz.com/)  \n- [Cracking the PM Interview](https://www.crackingthepminterview.com/)  \n- [Building Machine Learning Powered Applications](https://www.oreilly.com/library/view/building-machine-learning/9781492045106/)  \n- [People + AI Guidebook (Google Book)](https://pair.withgoogle.com/guidebook) [Interesting]  \n\n## Data Analysis \u0026 Data Science Books:\n- [Python for Data Analysis, 2nd Edition](https://www.oreilly.com/library/view/python-for-data/9781491957653/)     \n- [Data Science from Scratch, 2nd Edition](https://www.oreilly.com/library/view/data-science-from/9781492041122/)   \n- [Hands-On Exploratory Data Analysis with Python](https://www.packtpub.com/product/hands-on-exploratory-data-analysis-with-python/9781789537253)   \n\n## Web Scraping:\n- [Mining the Social Web, 3rd Edition](https://www.oreilly.com/library/view/mining-the-social/9781491973547/)   \n- [Web Scraping with Python, 2nd Edition](https://www.oreilly.com/library/view/web-scraping-with/9781491985564/)   \n- [Practical Web Scraping for Data Science, Apress Publisher](https://link.springer.com/book/10.1007/978-1-4842-3582-9)   \n\n## Python Programming Books:\n- [Python Tricks: The Book](https://dbader.org/products/) [Intermediate \u0026 Advanced Level, \u0026 **Great**]    \n- [Python 101](https://leanpub.com/py101/)   \n- [Python Crash Course, 2nd Edition](https://nostarch.com/pythoncrashcourse2e)    \n- [Daily Coding Problem](https://www.dailycodingproblem.com/blog/daily-coding-problem-book-now-available/) [Great]     \n- [Cracking the Coding Interview](https://www.crackingthecodinginterview.com/)   \n- [Cracking the Coding Interview - Solutions](https://github.com/careercup/CtCI-6th-Edition)   \n\n## Statistics:\n- [Practical Statistics for Data Scientists, 2nd Edition](https://www.oreilly.com/library/view/practical-statistics-for/9781492072935/)  \n- [Naked Statistics](https://wwnorton.com/books/naked-statistics/)  \n- [Bayesian Modeling and Computation in Python](https://bayesiancomputationbook.com/welcome.html)\n- [How to Lie with Statistics Book](https://www.google.nl/books/edition/How_to_Lie_with_Statistics/2oZGEAAAQBAJ?hl=en\u0026gbpv=1\u0026printsec=frontcover)  \n\n## Math Books:\n- [Everything You Always Wanted to Know About Mathematics](https://www.linkedin.com/posts/eric-vyacheslav-156273169_this-maths-book-is-trending-on-hacker-news-activity-7237822306553602050-GQLF?utm_source=share\u0026utm_medium=member_desktop)  \n\n## Other:\n- [Artificial Intelligence in Finance](https://www.oreilly.com/library/view/artificial-intelligence-in/9781492055426/) [Deep Learning + Finance \u0026 Data Science, Good, Programming + theory, O’Reilly Publisher]    \n- [Best Machine Learning Books (Updated for 2020)](https://blog.floydhub.com/best-machine-learning-books/)  \n- [Designing Machine Learning Systems](https://www.oreilly.com/library/view/designing-machine-learning/9781098107956/)  \n- [Deep Learning Interviews: Hundreds of fully solved job interview questions from a wide range of key topics in AI](https://arxiv.org/abs/2201.00650) [Interesting]   \n- [Harvard CS197: AI Research Experiences - The Course Book](https://docs.google.com/document/u/0/d/1uvAbEhbgS_M-uDMTzmOWRlYxqCkogKRXdbKYYT98ooc/mobilebasic#heading=h.bko37p9m9o8g) [**Excellent**]  \n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fahkarami%2Fgreat-deep-learning-books","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fahkarami%2Fgreat-deep-learning-books","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fahkarami%2Fgreat-deep-learning-books/lists"}