20130107 MLDM Monday

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  • 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● Its 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 ContentsChapter 1 Using RChapter 2 Data ExplorationChapter 3 Classification: Spam FilteringChapter 4 Ranking: Priority InboxChapter 5 Regression: Predicting Page ViewsChapter 6 Regularization: Text RegressionChapter 7 Optimization: Breaking CodesChapter 8 PCA: Building a Market IndexChapter 9 MDS: Visually Exploring US Senator SimilarityChapter 10 kNN: Recommendation SystemsChapter 11 Analyzing Social GraphsChapter 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. Todays 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