Vision: Machine Learning

Sunday, November 20, 2011

Machine Learning

Thanks to Sandeep for this good easy to Learn Layout .
This is Ideal Layout for learning new subjects , what this Layout provides
- complete set of handouts and corresponding Vidoes ,
- Videos are all in one page with hide/show. you can open 2 videos , press pause button on one video and can go to other video on that topic

Here comes my Perfectionist critic(asr) , how can we improve on this good Layout further
- we can have 2 pane window (same page) showing Lecture PDF on LEFT and on the Right showing Video
- Both panes do Vertical scroll independently that way you can go to any section of PDF and any related video for that section
- next step: Have 'topics' in each lecture PDF listed on a collapsible DIV so that we can go to those 'topics' directly.

What is Machine Learning?
A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P, if its performance at tasks in T, as measured by P, improves with experience E. - Tom M. Mitchell (1997).

Prerequisites
Following are the recommended prerequisites for this course:

Lecture handouts

cs229-notes1.pdf	Linear Regression, Classification and logistic regression, Generalized Linear Models
cs229-notes2.pdf	Generative Learning algorithms
cs229-notes3.pdf	Support Vector Machines
cs229-notes4.pdf	Learning Theory
cs229-notes5.pdf	Regularization and model selection
cs229-notes6.pdf	The perceptron and large margin classifiers
cs229-notes7a.pdf	The k-means clustering algorithm
cs229-notes7b.pdf	Mixtures of Gaussians and the EM algorithm
cs229-notes8.pdf	The EM algorithm
cs229-notes9.pdf	Factor analysis
cs229-notes10.pdf	Principal components analysis
cs229-notes11.pdf	Independent Components Analysis
cs229-notes12.pdf	Reinforcement Learning and Control