Introduction

이 페이지는 Mathematical Monk ML을 정리한 문서입니다. 관련 동영상이 궁금하신 분들은 아래 버튼을 눌러시면 됩니다.

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• Mathematical Monk ML

  Mar 30, 2016

  Mathematical Monk ML 정리사이트.

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Chapter 1

• (ML 1.1) Machine learning - overview and applications
• (ML 1.2) What is supervised learning?
• (ML 1.3) What is unsupervised learning?
• (ML 1.4) Variations on supervised and unsupervised
• (ML 1.5) Generative vs discriminative models
• (ML 1.6) k-Nearest Neighbor classification algorithm

Chapter 2

• (ML 2.1) Classification trees (CART)
• (ML 2.2) Regression trees (CART)
• (ML 2.3) Growing a regression tree (CART)
• (ML 2.4) Growing a classification tree (CART)
• (ML 2.5) Generalizations for trees (CART)
• (ML 2.6) Bootstrap aggregation (Bagging)
• (ML 2.7) Bagging for classification
• (ML 2.8) Random forests

Chapter 3

• (ML 3.1) Decision theory (Basic Framework)
• (ML 3.2) Minimizing conditional expected loss
• (ML 3.3) Choosing f to minimize expected loss
• (ML 3.4) Square loss
• (ML 3.5) The Big Picture (part 1)
• (ML 3.6) The Big Picture (part 2)
• (ML 3.7) The Big Picture (part 3)