参考资料:
[1] Russell, Stuart, and Peter Norvig. "Artificial intelligence: a modern approach." (1995),书籍
入门资料:
[1] 周志华. "机器学习." (2016),书籍(俗称西瓜书),配套公式推导:南瓜书
[2] Andrew Ng(Stanford). "CS229: Machine Learning ",在线课程(2018秋季版),中字视频:【斯坦福大学】CS229 机器学习
[3] 李宏毅. "机器学习",在线课程
深入学习:
[1] 机器学习白板推导,在线课程
[2] 李航. "统计学习方法." (2012),书籍
[3] Tom Mitchell. "Machine Learning." (1997),书籍
入门资料:
[1] 李沐 等. "动手学深度学习 第二版",书籍及在线课程
[2] Andrew Ng(Stanford). "CS230: Deep Learning",在线课程
深入学习:
[1] Ian Goodfellow, Yoshua Bengio, Aaron Courville. "深度学习"(2017),中译版,书籍(俗称花书)
参考资料:
[1] Road to Data Scientist,Roadmap
[2] Wes McKinney. 利用Python进行数据分析 第二版,中译版,书籍
自然语言处理:CS124: From Languages to Information,CS224d: Deep Learning for Natural Language Processing,与CS224n: Natural Language Processing with Deep Learning,在线课程
计算机视觉:CS231n: Convolutional Neural Networks for Visual Recognition,在线课程
时间序列处理:Adhikari, R., & Agrawal, R. K. (2013). An introductory study on time series modeling and forecasting. arXiv preprint arXiv:1302.6613.,文章;Introduction to Time Series Forecasting (Python),Deep Learning for Time Series Forecasting,Blogs
时空数据处理:W. Li, W. Tao, et.al., A Survey on Spatial and Spatiotemporal Prediction Methods,文章; X. Shi and D.-Y. Yeung, Machine learning for spatiotemporal sequence forecasting: A survey,文章。
图神经网络:Yao Ma, Jiliang Tang (2021). Deep Learning on Graphs,书籍;J. Zhou et al., Graph neural networks: A review of methods and applications,文章;Z. Wu, S. Pan et.al. A comprehensive survey on graph neural networks,文章。
可解释人工智能:AAAI2020 XAI Tutorial, CVPR2021 Interpretable Machine Learning for Computer Vision Tutorial, CVPR 2020 Interpretable Machine Learning for Computer Vision Tutorial,Tutorials
入门教程:
[1] Python基础教程|菜鸟教程
[2] 廖雪峰Python教程
深入学习:
入门教程:
[1] DEEP LEARNING WITH PYTORCH: A 60 MINUTE BLITZ
[2] Your First Deep Learning Project in Python with Keras Step-By-Step
[3] TensorFlow 2 Tutorial: Get Started in Deep Learning With tf.keras
[4] 动手学深度学习 PyTorch 实现,代码仓库
[5] 动手学深度学习 TensorFlow2.0 实现,代码仓库
参考资料为各个库的文档,且以最新英文版文档为宜(不要看中译版)。