1. 20121112 MLDM Monday
《Machine Learning for Hackers 》
導讀系列之一
by c3h3

2. TW useR Group & MLDM Monday
● http://www.meetup.com/Taiwan-useR-Group/
● http://www.facebook.com/TaiwanUseRGroup/
● http://www.youtube.com/user/TWuseRGroup/
● http://tw.use-r.net/

3. Why choose this book ?
● Case-Study Oriented
● It's about Machine Learning and Data
Mining (MLDM)
● It using R produce all the sample codes.

4. Sample Codes in book
● https://github.
com/johnmyleswhite/ML_for_Hackers

5. Table of Contents
Chapter 1 Using R
Chapter 2 Data Exploration
Chapter 3 Classification: Spam Filtering
Chapter 4 Ranking: Priority Inbox
Chapter 5 Regression: Predicting Page Views
Chapter 6 Regularization: Text Regression
Chapter 7 Optimization: Breaking Codes
Chapter 8 PCA: Building a Market Index
Chapter 9 MDS: Visually Exploring US Senator Similarity
Chapter 10 kNN: Recommendation Systems
Chapter 11 Analyzing Social Graphs
Chapter 12 Model Comparison

6. Table of Contents
● Basic R and Data Analysis
○ Chapter 1 Using R
○ Chapter 2 Data Exploration
● Supervised Learning
○ Chapter 3 Classification: Spam Filtering
○ Chapter 4 Ranking: Priority Inbox
○ Chapter 5 Regression: Predicting Page Views
○ Chapter 6 Regularization: Text Regression
○ Chapter 10 kNN: Recommendation Systems

7. Table of Contents
● Optimization Skills and Regularization
○ Chapter 7 Optimization: Breaking Codes
● Unsupervised Learning
○ Chapter 8 PCA: Building a Market Index
○ Chapter 9 MDS: Visually Exploring US Senator Similarity
○ Chapter 11 Analyzing Social Graphs
● Summary
○ Chapter 12 Model Comparison

8. ML for Hackers 導讀系列
● Basic R and Data Analysis
● Supervised Learning
○ Classification
○ Regression
● Optimization Skills and Regularization
● Unsupervised Learning
○ PCA
○ Clustering
○ Network Data Analysis
● Summary

9. Today's Outlines
● What is Machine Learning ?
○ Review: http://prezi.com/qkqps6z_i2bu/20130107-mldm-
monday/
● Basic Data Analysis in R
○ Basic Data Structures in R
○ Data Frame and Model Frame
● Two Example Data Set in Chapter 1 and Chapter 2
○ [Cleaning Data Practice] UFO Data Set
○ [Analysis Data Practice] Weights-Heights-Gander Data

10. Model Frame
● 看 Code 學寫 Code
○ source code of lm / rpart function
● Key functions for model frame
○ match.call(expand.dots = FALSE)
○ model.extract
● Reference
○ http://stat.ethz.ch/R-manual/R-patched/library/stats/html/model.extract.
html
○ http://stat.ethz.ch/R-manual/R-patched/library/base/html/match.call.html
○ http://stat.ethz.ch/R-manual/R-patched/library/stats/html/model.frame.html