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MIT18.01/18.02: Calculus
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📉 数学进阶
UCB CS70: discrete Math and probability theory
UCB CS126: probability theory
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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📐 数据结构与算法
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Coursera: Algorithms I & II
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UCB CS170: Efficient Algorithms and Intractable Problems
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MIT 6.031: Software Construction
UCB CS169: software engineering
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Coursera: Nand2Tetris
UCB CS61C: Great Ideas in Computer Architecture
ETHz: Digital Design and Computer Architecture
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Coursera: Machine Learning
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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📋 深度学习
UMich EECS 498-007 / 598-005: Deep Learning for Computer Vision
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国立台湾大学: 李宏毅机器学习
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Stanford CS224w: Machine Learning with Graphs
UCB CS285: Deep Reinforcement Learning
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🗡️ 机器学习进阶
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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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