Difference between revisions of "Course: Massive Data Analysis 2014"

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(Created page with '= CS-GY 6333 Massive Data Analysis: Tentative Schedule -- ''subject to change'' = * Course Web page: http://cs.nyu.edu/courses/spring14/CSCI-GA.2568-001/index.html * Instructo…')
 
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* Instructor: Professor Juliana Freire (http://vgc.poly.edu/~juliana/)
* Instructor: Professor Juliana Freire (http://vgc.poly.edu/~juliana/)


* Lecture: Mondays, 7:10pm-9:00pm at Cantor, room 101. ''Note new location!''
* Lecture: Mondays, 1:00pm-3:25pm at 2MTC, room 9.011.
** Cantor Film Center (CANTR), 36 E 8th St, New York, NY 10003
 
* Lab: Thursdays, 7:10pm-8:00pm at CIWW, room 109. ''Always bring your laptop.''
** Warren Weaver Hall (CIWW), 251 Mercer St, New York, NY 10012


= News =
= News =

Revision as of 01:44, 8 September 2014

CS-GY 6333 Massive Data Analysis: Tentative Schedule -- subject to change

  • Lecture: Mondays, 1:00pm-3:25pm at 2MTC, room 9.011.

News

  • The final exam will take place on May 12th.
  • We will have our last class on May 19th.
  • 4/21/2014: There are two new quizes on gradiance. They are due on 2014-04-28 23:59 PST.
  • Starting on Feb 10th, our class will meet at a new location: Cantor 101
  • We will have lab on Thu at CIWW, room 109. Bring your laptop!

Background (4 weeks)

Week 1 -- Jan 27: Course Overview; the evolution of Data Management


Week 2 -- Feb 3: Introduction to Databases

Week 3 -- Feb 10: Overview: Relational Model and SQL

  • Feb 13: Lab: Canceled -- University closed due to snow ==


Week 3.1 -- Feb 17: Holiday

Week 4 -- Feb 24: Overview: Advanced SQL and Query Optimization

Big Data Foundations and Infrastructure (2 weeks)

Week 5 -- Mar 3: Cloud computing, Map Reduce and Hadoop

  • Required reading:
    • Data-Intensive Text Processing with MapReduce, Chapters 1 and 2
    • Mining of Massive Datasets (2nd Edition), Chapter 2 - 2.1 and 2.2 (Large-Scale File Systems and Map-Reduce).
  • Homework Assignment -- Your first quiz is available on Gradiance. It is due on March 17th at 5pm.

Week 6 -- Mar 10: Algorithm Design for MapReduce

  • Required reading:
    • Data-Intensive Text Processing with MapReduce, Chapters 1 and 2
    • Mining of Massive Datasets (2nd Edition), Chapter 2.


Machine Learning and Big Data (3 weeks)

Week 7 -- Mar 23: Hashing and AllReduce

  • Invited lecture by John Langford

Week 8 -- Mar 30: Bandits

  • Invited lecture by John Langford

Week 9 -- Apr 7: Large Scale Machine Learning in the Real World

  • Invited lecture by Leon Bottou

Big Data Foundations and Infrastructure -- cont. (2 weeks)

Week 10 -- April 14: Parallel Databases vs MapReduce, Query Processing on Mapreduce and High-level Languages


Big Data Algorithms and Techniques (3 weeks)

Week 11 -- April 21: Data Management for Big Data (cont) and Association Rules

  • Homework Assignment -- Your quiz is available on Gradiance. It is due on April 28th.

Week 12 -- Apr 28: Finding similar items: Invited lecture by Dr. Harish Doraiswami

Week 13 -- May 5: Graph Analysis and Exam Review

Week 14 -- May 12: Final Exam

Week 15 -- May 19: Large-Scale Visualization -- Invited lecture by Dr. Lauro Lins (AT&T Research)

  • Reading:

The Value of Visualization, Jarke Van Wijk http://www.win.tue.nl/~vanwijk/vov.pdf

Tamara Munzner's Book draft 2 available online http://www.cs.ubc.ca/~tmm/courses/533/book/

Nanocubes Paper http://nanocubes.net http://nanocubes.net/assets/pdf/nanocubes_paper_preprint.pdf