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An AI engineer Prepares / 算法工程师自我修养
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courses's Introduction
An AI engineer Prepares / 算法工程师自我修养
1. NTU_Probability-I-II(**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,**大学,林轩田)
3. Probabilistic Graphical Models, Stanford University
4. CMU-11-785-Fall-2018, 11-485/785 Introduction to Deep Learning
5. CMU_PGM_Eric Xing, Probabilistic Graphical Models
7. Machine Learning, Andrew Ng
10. Deep-Learning-Specialization, Andrew Ng
11. Mathematics for Machine Learning
15. Machine Learning (2017,Spring), Hung-yi Lee
16. Machine Learning and having it deep and structured (2018,Spring), Hung-yi Lee
18. Machine Learning 专项课程
19. Advanced Machine Learning 专项课程
20. Machine Learning with TensorFlow on Google Cloud Platform 专项课程
21. Applied Data Science with Python 专项课程
23. CS294-158 Deep Unsupervised Learning Spring 2019
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
31. CS229T/STATS231: Statistical Learning Theory
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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