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UCB CS70: discrete Math and probability theory
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MIT 6.042J: Mathematics for Computer Science
MIT18.330: Introduction to numerical analysis
Standford EE364A: Convex Optimization
The Information Theory, Pattern Recognition, and Neural Networks
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Coursera: Nand2Tetris
UCB CS61C: Great Ideas in Computer Architecture
ETHz: Digital Design and Computer Architecture
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Stanford CS229: Machine Learning
UCB CS189: Introduction to Machine Learning
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CMU 10-414/714: Deep Learning Systems
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UMich EECS 498-007 / 598-005: Deep Learning for Computer Vision
Coursera: Deep Learning
国立台湾大学: 李宏毅机器学习
Stanford CS231n: CNN for Visual Recognition
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Stanford CS224w: Machine Learning with Graphs
UCB CS285: Deep Reinforcement Learning
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CMU 10-708: Probabilistic Graphical Models
Columbia STAT 8201: Deep Generative Models
U Toronto STA 4273 Winter 2021: Minimizing Expectations
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