Machine Learning 202

this 10-weeks course will cover several ML topics, including Bayesian Networks, Gradient Boosting, SVD, and recommender systems.

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We will cover several machine learning topics in detail. Among those are Bayesian Belief Networks, Prof. Jerome Friedman's gradient boosting papers, svd's and recommender systems.

For Machine Learning 202, we assume you are familiar with basic statistical concepts and have the ability to write programs running different algorithms on public data sets. We assume knowledge at the level of "Introduction to Data Mining" by Tan. If you have taken our Machine Learning 101, 102 classes and Machine Learning 201, you are well prepared for this course.

We expect you to have previously used R. We will use R for discussing homework problems and comparing different solution approaches - see cran.r-project.org/

The class will meet:
Wednesday and Thursday evenings.
from 7:00 pm to 9:00 pm
from 8/24/2011 - 9/22/2011

at Hacker Dojo, 140B S Whisman Road, Mountain View, CA

Class Fee: $300.00/per person

For a total of 10 meetings

for more information and to register - see
www.meetup.com/HandsOnProgrammingEvents/events/27922541/