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References
可以自行在下属列表找找到适合自己的学习资料，虽然罗列的比较多，但是个人最好选择一个深入阅读、练习。当练习到一定程度，可以再看看其他的资料，这样弥补单一学习资料可能存在的欠缺。
Python & IPython
- Python教程
- Python-Lectures
- A gallery of interesting Jupyter Notebooks
- IPython tutorials
- Examples from the IPython mini-book
- Code of the IPython Cookbook, Second Edition (2018)
- Essential Cheat Sheets for deep learning and machine learning researchers
- 手把手教你用Python做数据可视化
Libs
Machine learning
- ipython-notebooks: A collection of IPython notebooks covering various topics
- Learn Data Science
- AM207 2016
- Python机器学习
- scientific-python-lectures
Awesome series & Collections
Lectures
- Machine Learning
- CS229: Machine Learning
- CS 20: Tensorflow for Deep Learning Research
- CS 294: Deep Reinforcement Learning, UC Berkeley
- Deep Learning Book
- Machine Learning Crash Course with TensorFlow APIs
- Nvidia DLI
- Introduction to Machine Learning
- Computer Vision @ ETHZ
- SFMedu: A Structure from Motion System for Education
- Scene understanding of computer vision
- Autonomous Navigation for Flying Robots
- Multiple View Geometry
- Deep Learning for Self-Driving Cars
- 史上最全TensorFlow学习资源汇总
- Oxford Deep NLP 2017 course