Repository files navigation An AI engineer Prepares / 算法工程师自我修养 1. NTU_Probability-I-II(台湾大学，叶丙成， 顽想学概率一，二) 2. MachineLearing-Hsuan-Tien-Lin（机器学习基石&技法，台湾大学，林轩田） 3. Probabilistic Graphical Models, Stanford University 5. CMU_PGM_Eric Xing, Probabilistic Graphical Models 7. Machine Learning, Andrew Ng 10. Deep-Learning-Specialization, Andrew Ng 11. Mathematics for Machine Learning 17. Hands-on Introduction to Linux Commands and Shell Scripting 18. Advanced Machine Learning 专项课程 19. Programming in C++: A Hands-on Introduction 专项课程 21. Applied Data Science with Python 专项课程 24. Learn English: Intermediate Grammar 25. Fundamentals of Digital Image and Video Processing 27. Image and Video Processing: From Mars to Hollywood with a Stop at the Hospital 28. TensorFlow in Practice 30. Julia Scientific Programming 32. Computer Vision Specialization 33. Discrete Optimization 34. Fundamentals of Reinforcement Learning 35. CS224W: Machine Learning with Graphs 36. Generative Adversarial Networks (GANs)
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