Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
:robot: Roadmap to becoming a Machine Learning developer in 2020
| Date | Stars |
|---|---|
| 2026-07-31 | 453 |
| 2026-08-01 | 453 |
| 2026-08-06 | 453 |
Today
— stars today
This week
— stars this week
This month
— stars this month
Momentum
0.0
growth rate 0.00%/day
# ML-Roadmap Roadmap to becoming a Machine Learning developer in 2020 <div align="center"> <img src="https://github.com/JsonChao/ML-Roadmap/blob/master/Screenshot/20180115161718.png"> </div> ## Translations - [简体中文](https://github.com/JsonChao/ML-Roadmap/blob/master/README-CN.md) ## Introduction [Machine learning is Fun!](https://medium.com/@ageitgey/machine-learning-is-fun-80ea3ec3c471) [Data Science Simplified](https://becominghuman.ai/data-science-simplified-principles-and-process-b06304d63308) ## Data Analysis ### Concepts： [The Foundations of Data Science](http://data8.org/) [Computational and Inferential Thinking -The Foundations of Data Science](https://www.inferentialthinking.com/) ### Data Mining Algorithm： [LearnDataScience](https://github.com/nborwankar/LearnDataScience) [Algorithm Implementation](https://github.com/donnemartin/data-science-ipython-notebooks#scikit-learn) [Data-science-resources](https://www.datascienceweekly.org/data-science-resources/the-big-list-of-data-science-resources) ## Machine Learning [Andrew Ng-Machine Learning](https://www.coursera.org/learn/machine-learning) [Google-Machine Learning Crash Course](https://developers.google.cn/machine-learning/crash-course/) [Carnegie Mellon University-Machine Learning](http://www.cs.cmu.edu/~tom/10701_sp11/lectures.shtml) ## Deep Learning [Udacity-Deep Learning](https://www.udacity.com/course/deep-learning--ud730) ## Learning From Data [Learning From Data](http://work.caltech.edu/lectures.html) ## Neural Networks [Youtube-Neural Networks](https://www.youtube.com/playlist?list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH) ## University Course ### Stanford University： [《Statistical Learning》](https://lagunita.stanford.edu/courses/HumanitiesandScience/StatLearning/Winter2015/about) [《Machine Learning》](http://cs229.stanford.edu/) [《Convolutional Neural Networks》](http://cs231n.stanford.edu/) [《Deep Leanring for Natural Language Processing》](http://cs224d.stanford.edu/) ### MIT University： [《Introduction to neural networks》](http://ocw.mit.edu/courses/brain-and-cognitive-sciences/9-641j-introduction-to-neural-networks-spring-2005/index.htm) [《Machine Learning》](http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-867-machine-learning-fall-2006/) [《Prediction》](http://ocw.mit.edu/courses/sloan-school-of-management/15-097-prediction-machine-learning-and-statistics-spring-2012/index.htm) ### More Courses： [awesome-machine-learning](https://github.com/RatulGhosh/awesome-machine-learning) ## Books ### Machine Learning： [Pattern Recognition and Machine Learning](https://book.douban.com/subject/2061116/) [PDF](http://users.isr.ist.utl.pt/~wurmd/Livros/school/Bishop%20-%20Pattern%20Recognition%20And%20Machine%20Learning%20-%20Springer%20%202006.pdf) [Matlab Implementation](https://github.com/PRML/PRMLT) [Introduction to Machine Learning with Python](https://book.douban.com/subject/26279609/) [Hands-On Machine Learning with Scikit-Learn and TensorFlow](https://book.douban.com/subject/26840215/) ### Manual： [understanding-machine-learning-theory-algorithms](https://www.cs.huji.ac.il/~shais/UnderstandingMachineLearning/understanding-machine-learning-theory-algorithms.pdf) [ESLII](https://web.stanford.edu/~hastie/Papers/ESLII.pdf) ### Deep Learning： [《Deep Learning》](https://book.douban.com/subject/27087503/) [Official website](http://www.deeplearningbook.org/) ### Neural Networks： [Introduction-Neural Networks and Deep Learning](http://neuralnetworksanddeeplearning.com/) ## Articles/Small Videos [Google TensorFlow](https://www.youtube.com/playlist?list=PLOU2XLYxmsIIuiBfYad6rFYQU_jL2ryal) [Machine-learning-tutorial-python-introduction](https://pythonprogramming.net/machine-learning-tutorial-python-introduction/) [machine-learning-algorithm](https://medium.com/machine-learning-101) [machine-learning-for-humans](https://medium.com/machine-learning-for-humans) [Rules of Machine Learning: Best Practices for M
Excerpt of 8,116 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:8948568a75f2d326, topic:roadmap, readme:tutorial, readme:course
matched fp:8948568a75f2d326, topic:neural-network