# Quick start guide(Video Links)

The following knowledge is prerequisite to make any sense out of Machine learning

**Linear Algebra by Gilbert Strang**: http://ocw.mit.edu/courses/mathematics/18-06-linear-algebra-spring-2010/video-lectures/**Convex Optimization by Boyd**http://see.stanford.edu/see/courseinfo.aspx?coll=2db7ced4-39d1-4fdb-90e8-364129597c87**Probability and statistics for ML**: http://videolectures.net/bootcamp07_keller_bss/**Some mathematical tools for ML**: http://videolectures.net/mlss03_burges_smtml/ Video+Audio Very bad quality**Probability primer**(measure theory and probability theory) : http://www.youtube.com/playlist?list=PL17567A1A3F5DB5E4&feature=plcp

Once the prerequisites are complete, the following are good series of lectures on Machine Learning.

### Basic ML:

**Andrew Ng’s Video Lectures(CS229)**: http://see.stanford.edu/see/courseinfo.aspx?coll=348ca38a-3a6d-4052-937d-cb017338d7b1**Andrew Ng’s online course offering**: http://www.ml-class.org**Tom Mitchell’s video lectures(10-701)**: http://www.cs.cmu.edu/~tom/10701_sp11/lectures.shtml**Mathematicalmonk’s videos**: http://www.youtube.com/playlist?list=PLD0F06AA0D2E8FFBA&feature=plpp

### Advanced ML:

**SVMs and kernel methods**,**Scholkopf**: http://videolectures.net/mlss03_scholkopf_lk/

basics for Support Vector Machines and related Kernel methods. Video+Audio Very bad quality**Kernel methods and Support Vector Machines, Smola:**http://videolectures.net/mlss08au_smola_ksvm/

Introduction of the main ideas of statistical learning theory, Support Vector Machines, Kernel Feature Spaces, An overview of the applications of Kernel Methods.**Easily one of the best talks on SVM. Almost like a run-down tutorial.**http://videolectures.net/mlss06tw_lin_svm/**Introduction to Learning Theory, Olivier Bousquet**. http://videolectures.net/mlss06au_bousquet_ilt/

This tutorial focuses on the “larger picture” than on mathematical proofs, it is not restricted to statistical learning theory however. 5 lectures.**Statistical Learning Theory,**Olivier Bousquet, http://videolectures.net/mlss07_bousquet_slt/

This course gives a detailed introduction to Learning Theory with a focus on the Classification problem.**Statistical Learning Theory, John-Shawe Taylor**, University of London. 7 lectures. http://videolectures.net/mlss04_taylor_slt/**Advanced Statistical Learning Theory, Oliver Bousquet.**3 Lectures. http://videolectures.net/mlss04_bousquet_aslt/

Most of the above links have been filtered from http://onionesquereality.wordpress.com/2008/08/31/demystifying-support-vector-machines-for-beginners/

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