machine-learning-foundations
Introduction
課程設計理念
When Can Machine Learn?
Basic Learning Model
Classification
Why Can Machine Learn?
Perceptron Learning Algorithm
Is Learning Feasible?
Vapnik-Chervonenkis (VC) bound
VC Dimension
Noise and Error
How Can Machines Learn?
Linear Regression
Linear Classification vs. Linear Regression
Logistic Regression
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Why Can Machine Learn?
Why Can Machine Learn?
這個章節我們將導入許多的數學工具, 來幫助我們瞭解在學習 Model 中, 我們為何可以學習? (改善某個可量化評估的事情), 又在什麼樣的條件限制下, 我們才可以做到機器學習。
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