ISLR :: 소개 및 강좌

Published by onesixx on

Course:  https://lagunita.stanford.edu/courses/HumanitiesSciences/StatLearning/Winter2016/about
                 https://www.r-bloggers.com/in-depth-introduction-to-machine-learning-in-15-hours-of-expert-videos/
Book:    www.StatLearning.com   http://www-bcf.usc.edu/~gareth/ISL/
             http://www.springer.com/series/417
번역본: 가볍게 시작하는 통계학습   (컬러가 아닌게 함정)
참고:  http://www.alsharif.info/iom530

 

ISL Cover 2An Introduction to Statistical Learning, with Applications in R”
(James, Witten, Hastie, Tibshirani – Springer 2013

W1: Introduction and Overview of Statistical Learning (Chapters 1-2)
W2: Linear Regression (Chapter 3)
W3: Classification (Chapter 4)
W4: Resampling Methods (Chapter 5)
W5: Linear Model Selection and Regularization (Chapter 6)
W6: Moving Beyong Linearity (Chapter 7)
W7: Tree-based Methods (Chapter 8)
W8: Support Vector Machines (Chapter 9)
W9: Unsupervised Learning (Chapter 10)

 

Chapter 1: Introduction (slidesplaylist)

Chapter 2: Statistical Learning (slidesplaylist)

Chapter 3: Linear Regression (slidesplaylist)

Chapter 4: Classification (slidesplaylist)

Chapter 5: Resampling Methods (slidesplaylist)

Chapter 6: Linear Model Selection and Regularization (slidesplaylist)

Chapter 7: Moving Beyond Linearity (slidesplaylist)

Chapter 8: Tree-Based Methods (slidesplaylist)

Chapter 9: Support Vector Machines (slidesplaylist)

Chapter 10: Unsupervised Learning (slidesplaylist)

Interviews (playlist)

 

참고> http://psystat.tistory.com/category/R/ISLR

 

Categories: book:ISLR

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