同类别比较
名称	排名	指标
qfettes/DeepRL-Tutorials	11,713	语言: Jupyter Notebook 星标数: 1,080 分叉数: 325 简介: Contains high quality implementations of Deep Reinforcement Learning algorithms written in PyTorch
curiousily/Deep-Learning-For-Hackers	11,722	语言: Jupyter Notebook 星标数: 1,078 分叉数: 431 简介: Machine Learning tutorials with TensorFlow 2 and Keras in Python (Jupyter notebooks included) - (LSTMs, Hyperameter tuning, Data preprocessing, Bias-variance tradeoff, Anomaly Detection, Autoencoders, Time Series Forecasting, Object Detection, Sentiment Analysis, Intent Recognition with BERT)
Akramz/Hands-on-Machine-Learning-with-Scikit-Learn-Keras-and-TensorFlow	11,736	语言: Jupyter Notebook 星标数: 1,075 分叉数: 421 简介: Notes & exercise solutions of Part I from the book: "Hands-On ML with Scikit-Learn, Keras & TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems" by Aurelien Geron
Devinterview-io/llms-interview-questions	11,737	星标数: 1,075 分叉数: 120 简介: 🟣 LLMs interview questions and answers to help you prepare for your next machine learning and data science interview in 2026.
zlotus/notes-LSJU-machine-learning	11,776	语言: Jupyter Notebook 星标数: 1,069 分叉数: 388 简介: 机器学习笔记
DjangoPeng/LLM-quickstart	11,785	语言: Jupyter Notebook 星标数: 1,067 分叉数: 591 简介: Quick Start for Large Language Models (Theoretical Learning and Practical Fine-tuning) 大语言模型快速入门（理论学习与微调实战）
robbiebarrat/rapping-neural-network	11,787	语言: Python 星标数: 1,067 分叉数: 162 简介: Rap song writing recurrent neural network trained on Kanye West's entire discography
khuangaf/CryptocurrencyPrediction	11,805	语言: Jupyter Notebook 星标数: 1,064 分叉数: 364 简介: Predict Cryptocurrency Price with Deep Learning

名称

排名

指标

11,713

语言:: Jupyter Notebook
星标数:: 1,080
分叉数:: 325
简介:: Contains high quality implementations of Deep Reinforcement Learning algorithms written in PyTorch

curiousily/Deep-Learning-For-Hackers

11,722

语言:: Jupyter Notebook
星标数:: 1,078
分叉数:: 431
简介:: Machine Learning tutorials with TensorFlow 2 and Keras in Python (Jupyter notebooks included) - (LSTMs, Hyperameter tuning, Data preprocessing, Bias-variance tradeoff, Anomaly Detection, Autoencoders, Time Series Forecasting, Object Detection, Sentiment Analysis, Intent Recognition with BERT)

Akramz/Hands-on-Machine-Learning-with-Scikit-Learn-Keras-and-TensorFlow

11,736

语言:: Jupyter Notebook
星标数:: 1,075
分叉数:: 421
简介:: Notes & exercise solutions of Part I from the book: "Hands-On ML with Scikit-Learn, Keras & TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems" by Aurelien Geron

Devinterview-io/llms-interview-questions

11,737

星标数:: 1,075
分叉数:: 120
简介:: 🟣 LLMs interview questions and answers to help you prepare for your next machine learning and data science interview in 2026.

zlotus/notes-LSJU-machine-learning

11,776

语言:: Jupyter Notebook
星标数:: 1,069
分叉数:: 388
简介:: 机器学习笔记

DjangoPeng/LLM-quickstart

11,785

语言:: Jupyter Notebook
星标数:: 1,067
分叉数:: 591
简介:: Quick Start for Large Language Models (Theoretical Learning and Practical Fine-tuning) 大语言模型快速入门（理论学习与微调实战）

robbiebarrat/rapping-neural-network

11,787

语言:: Python
星标数:: 1,067
分叉数:: 162
简介:: Rap song writing recurrent neural network trained on Kanye West's entire discography

khuangaf/CryptocurrencyPrediction

11,805

语言:: Jupyter Notebook
星标数:: 1,064
分叉数:: 364
简介:: Predict Cryptocurrency Price with Deep Learning

关键参数与规格
参数	值
语言	Jupyter Notebook
类别	Tutorials
子类别	ML/AI fundamentals
星标数	1,070
分叉数	312
贡献者	2
创建日期	2017-10-27
更新日期	2026-10-09
1 天星标数	0
7 天星标数	2
排名	11,760
上次排名	11,688
排名变化	-72
7 天星标排名	8,252
上次 7 天星标排名	8,322
7 天星标排名变化	70
总星标排名	10,584
上次总星标排名	10,573
总星标排名变化	-11
国家	India

参数

值

语言

Jupyter Notebook

类别

Tutorials

子类别

ML/AI fundamentals

星标数

1,070

分叉数

312

贡献者

创建日期

2017-10-27

更新日期

2026-10-09

1 天星标数

7 天星标数

排名

11,760

上次排名

11,688

排名变化

-72

7 天星标排名

8,252

上次 7 天星标排名

8,322

7 天星标排名变化

总星标排名

10,584

上次总星标排名

10,573

总星标排名变化

-11

国家

India

Deep-Learning-Book-Chapter-Summaries

This repository provides a summary for each chapter of the Deep Learning book by Ian Goodfellow, Yoshua Bengio and Aaron Courville and attempts to explain some of the concepts in greater detail. Some of the tougher chapters have blog post(s) dedicated to them which can be found on http://medium.com/inveterate-learner.

Chapters

Part I: Applied Math and Machine Learning Basics
- Chapter 2: Linear Algebra [chapter]
- Chapter 3: Probability and Information Theory [chapter]
- Chapter 4: Numerical Computation [chapter]
- Chapter 5: Machine Learning Basics [chapter]
Part II: Modern Practical Deep Networks
- Chapter 6: Deep Feedforward Networks [chapter]
- Chapter 7: Regularization for Deep Learning [chapter]
- Chapter 8: Optimization for Training Deep Models [chapter]
- Chapter 9: Convolutional Networks [chapter]
- Chapter 10: Sequence Modeling: Recurrent and Recursive Nets [chapter]
- Chapter 11: Practical Methodology [chapter]
- Chapter 12: Applications [chapter]
Part III: Deep Learning Research
- Chapter 13: Linear Factor Models [chapter]
- Chapter 14: Autoencoders [chapter]
- Chapter 15: Representation Learning [chapter]
- Chapter 16: Structured Probabilistic Models for Deep Learning [chapter]
- Chapter 17: Monte Carlo Methods [chapter]
- Chapter 18: Confronting the Partition Function [chapter]
- Chapter 19: Approximate Inference [chapter]
- Chapter 20: Deep Generative Models [chapter]

Contributors

Contributing

Please feel free to open a Pull Request to contribute a summary for the chapters 5, 6 and 12 as we might not be able to cover them owing to other commitments. Also, if you think there's any section that requires more/better explanation, please use the issue tracker to let us know about the same.

Support

If you like this repo and find it useful, please consider (★) starring it (on top right of the page) so that it can reach a broader audience.

Deep-Learning-Book-Chapter-Summaries

记录了多少星标和分叉？

仓库排名是多少？

记录的语言和类别是什么？

哪个仓库排名最接近？

Deep-Learning-Book-Chapter-Summaries

Chapters

Contributors

Contributing

Support