Summary of machine learning materials

1 summary

This paper aims to summarize my usual machine learning reference materials , It's convenient for you to check it at any time 、 to update , At the same time, it is also shared with friends in need . This article will be updated from time to time , Ensure timeliness of content .

2 Online courses

• Standford CS 229: Machine Learning - Bilibili：https://www.bilibili.com/video/BV1pp4y1t7Na?spm_id_from=333.337.search-card.all.click
• Learn from Li Mu AI - Bilibili：https://space.bilibili.com/1567748478/channel/series
• TensorFlow Developer Certificate Course - Zero to Mastery：https://dbourke.link/ZTMTFcourse
• Intro to TensorFlow for Deep Learning - Udacity：https://www.udacity.com/course/intro-to-tensorflow-for-deep-learning--ud187
• Machine Learning Crash Course - Google：https://developers.google.com/machine-learning/crash-course
• Machine Learning for Beginners - Microsoft：https://microsoft.github.io/ML-For-Beginners/#/
• Data Science for Beginners - Microsoft：https://microsoft.github.io/Data-Science-For-Beginners/#/

3 Technology blogs & e-book

Technology blogs ：

• Visualizing machine learning one concept at a time - Jay Alammar：http://jalammar.github.io/
• Han Xiao tech blog：https://hanxiao.io/
• Google AI：https://blog.google/technology/ai/
• Open AI：https://openai.com/
• The Unofficial Google Data Science Blog：https://www.unofficialgoogledatascience.com/

e-book ：

• TensorFlow Developer Certificate Learning E-book：https://dev.mrdbourke.com/tensorflow-deep-learning/
• Simple and crude TensorFlow 2 | A Concise Handbook of TensorFlow 2：https://tf.wiki/
• 30 God, eat that one TensorFlow2：https://lyhue1991.github.io/eat_tensorflow2_in_30_days/chinese/
• Machine Learning Interviews Book：https://huyenchip.com/ml-interviews-book/
• Hands-on deep learning - Amazon：https://zh-v2.d2l.ai/
• HuggingFace Course：https://huggingface.co/course/chapter1/1
• Forecasting: Principles and Practice - 3rd Edition：https://otexts.com/fpp3/index.html
• Rules of Machine Learning：https://developers.google.com/machine-learning/guides/rules-of-ml#terminology

4 GitHub resources

• Data-Science-For-Beginners - Microsoft：https://github.com/microsoft/Data-Science-For-Beginners
• ML-For-Beginners - Microsoft：https://github.com/microsoft/ML-For-Beginners
• Hands-on Machine Learning with Scikit-Learn, Keras and TensorFlow：https://github.com/ageron/handson-ml2
• TensorFlow In Practice：https://github.com/lmoroney/dlaicourse

5 Notion note

• TensorFlow in Practice on Coursera Notes：https://www.notion.so/Course-TensorFlow-in-Practice-on-Coursera-Notes-5f4f8915fe3342e2a69f75ef1986ba3b
• MIT Introduction to Deep Learning Notes：https://www.notion.so/Course-MIT-Introduction-to-Deep-Learning-Notes-0e48ecc9ed7342b7b448956bed9e0e75

6 summary

This article will be updated continuously , Also welcome to share your common resources below .