Machine Learning: From Theory To Application 機器學習筆記
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- [Preface](/HZy0acV9SICnLDyQhp0QfQ)
- [0-1: Introduction to Machine Learning](/6AboF9JBRSiuN622LWxstA)
- [0-2: Optimization](/-QqfUs3pT3aQ1HWMirlfrw)
Chapter 1: Introduction to Statistical Learning Theory
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- [1-1: Learning Framework for Supervised Learning](/eYKmDbrPQyalEEkP5e0w_Q)
- [1-2: Generalization: PAC learning](/BzMW5LK3Q0mOXvhJYPWD6w)
- [1-3: Growth Function and VC Dimension](/a29c0H1bTSS0bfuqrOEQRw)
- [1-4: Rademacher Complexity](/oox2ztRmQHaB3F3k3khgRA)
Chapter 2: Classification and Regression
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- [2-1: Linear Classifiers](/qaPNLkPARgGyXkQ_3gFwdw)
- [2-2: Support Vector Machine (SVM)](/Oxbn21k8TqayBpojUU0wnQ)
Chapter 3: Generative learning
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Chapter 4: Introduction to Deep Learning
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Chapter 5: Unsupervised Learning
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Clustering
Dimensionality Reduction
Chapter 6: Reinforcement Learning
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