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Handouts:

• Basic Math recitation Slides
• Hadoop session Slides, Example, Hadoop Installation Instructions

• 1/3/2011 Introduction [PDF], MapReduce [PDF]
  Reading: Ch2: Large-Scale File Systems and Map-Reduce
• 1/5/2011 Association Rules: Frequent itemsets and Association rules [PDF]
  Reading: Ch6: Frequent itemsets
• 1/10/2011 Near Neighbor Search in High Dimensional Data [PDF]
  Reading: Ch3: Finding Similar Items
• 1/12/2011 Locality Sensitive Hashing (LSH) [PDF]
  Reading: Ch3: Finding Similar Items
• 1/17/2011 Martin Luther King, Jr., Day (no class)
• 1/19/2011 Theory of Locality Sensitive Hashing [PDF]
  Reading: Ch3: Finding Similar Items
• 1/24/2011 Dimensionality reduction: SVD and CUR [PDF]
  Reading: Some uses of spectral methods by Abhiram Ranade
• 1/26/2011 Clustering [PDF]
  Reading: Ch7: Clustering
• 1/31/2011 Recommendation Systems [PDF]
  Reading: Ch9: Recommendation systems and The Long Tail in Wired.
• 2/2/2011 Recommendation Systems (Netflix challenge) [PDF]
  Reading: Ch9: Recommendation systems
• 2/7/2011 Link Analysis, PageRank, Hubs and Authorities [PDF]
  Reading: Ch5: Link Analysis
• 2/9/2011 Web spam and TrustRank, Random Walks with Restarts [PDF]
  Reading: Ch5: Link Analysis
• 2/14/2011 Large scale supervised machine learning (1): k-nearest neighbor, Perceptron [PDF]
• 2/16/2011 Large scale supervised machine learning (2): Support Vector Machines [PDF]
• 2/21/2011 Presidents' Day (no class)
• 2/23/2011 Large scale supervised machine learning (3): Classification and regression trees [PDF]
  Reading: PLANET: Massively Parallel Learning of Tree Ensembles with MapReduce by Panda, Herbach, Basu and Bayardo. VLDB 2009.
• 2/28/2011 Mining data streams (1) [PDF]
  Reading: Ch4: Mining data streams
• 3/2/2011 Mining data streams (2) [PDF]
  Reading: Ch4: Mining data streams
• 3/7/2011 Web Advertising [PDF]
  Reading: Ch8:Advertising on the Web
• 3/9/2011 Review session [PDF]