教程

教程 #

基础 #

[book]d2l-ai/d2l-en

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dive into deep learning

[book]d2l-ai/d2l-zh

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动手学深度学习

[book]dod-o/statistical-learning-method_code

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手写实现李航《统计学习方法》书中全部算法

[video]shuhuai007/machine-learning-session

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【机器学习】【白板推导系列】【合集 1 ~ 23】

tsyw/MachineLearningNotes

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My personal notes

Bilibili - 机器学习白板系列


[video]

机器学习教程(小象学院) #


josephmisiti/awesome-machine-learning

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ZuzooVn/machine-learning-for-software-engineers

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A complete daily plan for studying to become a machine learning engineer.


ageron/handson-ml

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A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.


fighting41love/funNLP

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NLP 民工的乐园:几乎最全的中文 NLP 资源库


eriklindernoren/ML-From-Scratch

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Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.


trekhleb/homemade-machine-learning

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Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained.


kailashahirwar/cheatsheets-ai

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Essential Cheat Sheets for deep learning and machine learning researchers

https://medium.com/@kailashahirwar/essential-cheat-sheets-for-machine-learning-and-deep-learning-researchers-efb6a8ebd2e5

https://aicheatsheets.com


rasbt/python-machine-learning-book

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The “Python Machine Learning (1st edition)” book code repository and info resource


afshinea/stanford-cs-229-machine-learning #

!Github stars

VIP cheatsheets for Stanford’s CS 229 Machine Learning https://stanford.edu/~shervine/teaching/cs-229/


ujjwalkarn/Machine-Learning-Tutorials

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machine learning and deep learning tutorials, articles and other resources http://ujjwalkarn.github.io/Machine-Learning-Tutorials/


janishar/mit-deep-learning-book-pdf

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MIT Deep Learning Book in PDF format (complete and parts) by Ian Goodfellow, Yoshua Bengio and Aaron Courville


进阶 #

[book]christophm/interpretable-ml-book

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Book about interpretable machine learning https://christophm.github.io/interpretable-ml-book/

[book]mingchaozhu/interpretablemlbook

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该书为《Interpretable Machine Learning》中文版。该书原作者是 Christoph Molnar,他是一名统计学家和机器学习者 @christophM。该书的项目  地址,这是一个很棒的工作。你可以在 releases 中下载本书英文版  pdf

我是 朱明超,同样,我也是一名机器学习者。关于此书的译本,我在翻译后进行了校正。如果你在英文原书中看到某些表述问题,可以参考我在中文书里的描述。当然,由于英文原书是较早前出版的,本书并不是完全基于英文书,作者 Christoph Molnar 在《Interpretable Machine Learning》的  网页版  中对内容不断填充,所以中文版的翻译主要基于网页版 (内容会多于英文书)。你可以在 releases 中下载本书中文版  pdf


hangtwenty/dive-into-machine-learning

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Dive into Machine Learning with Python Jupyter notebook and scikit-learn! http://hangtwenty.github.io/dive-into-machine-learning/


RedditSota/state-of-the-art-result-for-machine-learning-problems

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This repository provides state of the art (SoTA) results for all machine learning problems.


scutan90/DeepLearning-500-questions

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深度学习 500 问,以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述

rushter/MLAlgorithms

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Minimal and clean examples of machine learning algorithms implementations