Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
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D2l En | 16,954 | 11 days ago | 83 | other | Python | |||||
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 400 universities from 60 countries including Stanford, MIT, Harvard, and Cambridge. | ||||||||||
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Eat_tensorflow2_in_30_days | 9,591 | 6 months ago | 25 | apache-2.0 | Python | |||||
Tensorflow2.0 🍎🍊 is delicious, just eat it! 😋😋 | ||||||||||
Pyprobml | 5,491 | 14 days ago | 30 | mit | Jupyter Notebook | |||||
Python code for "Probabilistic Machine learning" book by Kevin Murphy | ||||||||||
Tensorflow Book | 4,443 | 3 years ago | 14 | mit | Jupyter Notebook | |||||
Accompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations. | ||||||||||
Hands On Ml Zh | 3,703 | 2 years ago | 1 | September 21, 2020 | 19 | CSS | ||||
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Python Machine Learning Book 3rd Edition | 3,637 | 5 months ago | 19 | mit | Jupyter Notebook | |||||
The "Python Machine Learning (3rd edition)" book code repository | ||||||||||
Deep Learning Book | 2,650 | 4 years ago | 1 | December 24, 2016 | 2 | other | Jupyter Notebook | |||
Repository for "Introduction to Artificial Neural Networks and Deep Learning: A Practical Guide with Applications in Python" | ||||||||||
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Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system. | ||||||||||
Rl Book | 692 | 5 months ago | HTML | |||||||
Source codes for the book "Reinforcement Learning: Theory and Python Implementation" |
Getting Started • About • Table of Contents • Donate • Acknowledgment • FAQ •
This is the GitHub version of the Deep Learning with Tensorflow 2.0 by Mukesh Mithrakumar. Feel free to watch for updates, you can also follow me to get notified when I make a new post.
Read the book in its entirety online at https://www.adhiraiyan.org/DeepLearningWithTensorflow.html
Run the code using the Jupyter notebooks available in this repository's notebooks directory.
Launch executable versions of these notebooks using Google Colab:
Launch a live notebook server with these notebooks using binder:
This Book is a practical guide to Deep Learning with Tensorflow 2.0. We will be using the Deep Learning Book by Ian Goodfellow as our guide. Ian Goodfellows' Deep Learning Book is an excellent, comprehensive textbook on deep learning that I found so far but this book can be challenging because this is a highly theoretical book written as an academic text and the best way to learn these concepts would be by practicing it, working on problems and solving programming examples which resulted in me writing Deep Learning with Tensorflow 2.0 as a practical guide with explanations for complex concepts, summaries for others and practical examples and exercises in Tensorflow 2.0 to help anyone with limited mathematics, machine learning and programming background to get started.
Read more about the book in Introduction.
Finally I would like to ask for your help, this Book is for you, and I would love to hear from you, if you need more explanations, have doubts on certain sections, many others will feel the same so please feel free to reach out to me via:
with your questions, comments or even if you just want to say Hi.
To cite the Deep Learning Book by GoodFellow, please use this bibtex entry:
@book{Goodfellow-et-al-2016,
title={Deep Learning},
author={Ian Goodfellow and Yoshua Bengio and Aaron Courville},
publisher={MIT Press},
note={\url{http://www.deeplearningbook.org}},
year={2016}
}
To cite the Deep Learning with Tensorflow 2.0 Book by Mukesh Mithrakumar, please use this bibtex entry:
@book{MukeshMithrakumar-2019,
title={Deep Learning with Tensorflow 2.0},
author={Mukesh Mithrakumar},
note={\url{https://github.com/adhiraiyan/DeepLearningWithTF2.0}},
year={2019}
}