Difference between revisions of "Course: Big Data Analysis"

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(Created page with ''''''Make sure to check my.poly.edu for course announcements''''' '== Week 1: Monday Sept. 10th --- Course Overview == * Course overview (First day of classes!) * Student sur…')
 
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* Data-Intensive Text Processing with MapReduce, Chapter 2
* Data-Intensive Text Processing with MapReduce, Chapter 2


== Week 3: Monday Sept. 24th -- "Statistics is easy" ==
== Week 3: Monday Sept. 24th --- Statistics is easy ==


* Guest lecture by [http://cs.nyu.edu/shasha/ Dennis Shasha]
* Guest lecture by [http://cs.nyu.edu/shasha/ Dennis Shasha]
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* http://www.morganclaypool.com/doi/abs/10.2200/S00142ED1V01Y200807MAS001 -- book is available for free for NYU students  
* http://www.morganclaypool.com/doi/abs/10.2200/S00142ED1V01Y200807MAS001 -- book is available for free for NYU students  
* JF: add references for issues related to stats and big data
* JF: add references for issues related to stats and big data


== Week 4:  Monday Oct. 1st -- Databases and Big Data ==
== Week 4:  Monday Oct. 1st -- Databases and Big Data ==

Revision as of 00:09, 27 August 2012

Make sure to check my.poly.edu for course announcements

'== Week 1: Monday Sept. 10th --- Course Overview ==

  • Course overview (First day of classes!)
  • Student survey
  • Introduction to Big Data

Week 2: Monday Sept. 17th --- Map-Reduce

  • Introduction to map-reduce

Readings

  • google original paper
  • Mining of Massive Datasets, Chapter 2
  • Data-Intensive Text Processing with MapReduce, Chapter 2

Week 3: Monday Sept. 24th --- Statistics is easy

Readings

Week 4: Monday Oct. 1st -- Databases and Big Data

  • Databases and Big Data

Readings

  • JF: ADD: NoSQL databases (reading papers from literature)

Column store vs. tuple store. HBase, MongoDB, VaultDB, Cassandra, HadoopDB (Facebook) Overview of different architectures, distributed databases vs. hadoop, transaction support...

Week 5: Monday Oct. 8st --- Finding Similar Items

  • Overview of information integration

Readings

  • Mining of Massive Datasets, chapter 3; information integration; entity resolution


Week 6: Monday Oct. 15st --- Graph Analysis

  • Graph algorithms, link analysis, social networks

Readings

  • Mining of Massive Datasets, Chapter 5
  • Data-Intensive Text Processing with MapReduce, Chapter 5


Week 7: Monday Oct. 22st --- Introduction to Visualization; Data stewardship and provenance

  • Guest lecture by Claudio Silva and Lauro Lins

Readings

  • Hellerstein (ask Claudio for additional references)
  • ADD: provenance and reproducibility


Week 8: Monday Oct. 29th --- TBD swap oct 15

  • Reading: inverted index and crawling (Lin chapter 4)
  • Ask Torsten (tentative, ask him for reading material)

Readings

  • Data-Intensive Text Processing with MapReduce, Chapter 4


Week 9: Monday Nov. 12th --- Frequent Itemsets

Reading

  • Mining of Massive Datasets, Chapter 6


Week 10: Monday Nov. 5th --- Mining Data Streams =

Readings

  • Mining of Massive Datasets, Chapter 4


Week 11: Monday Nov. 19th --- Clustering

Readings

  • Mining of Massive Datasets, Chapter 7

Week 12: Monday Nov. 26th --- Recommendation Systems

Readings

  • Mining of Massive Datasets, Chapter 9

Week 13 Monday Dec. 3rd --- EM algorithms for text processing=

  • Data-Intensive Text Processing with MapReduce, Chapter 6

== Week 14 == Monday Dec. 10th

  • Project presentation