Soft Margin SVM and Kernels with CVXOPT 
Soft Margin SVM and Kernels with CVXOPT
by Harrison Kinsley
Video Lecture 32 of 42
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Date Added: August 11, 2016

Lecture Description

In this tutorial, we cover the Soft Margin SVM, along with Kernels and quadratic programming with CVXOPT all in one quick tutorial using some example code from:
www.mblondel.org/journal/2010/09/19/support-vector-machines-in-python/

Visualizing the conversion of many dimensions back to 2D: www.youtube.com/watch?v=3liCbRZPrZA

Quadratic programming with CVXOPT: cvxopt.org/userguide/coneprog.html#quadratic-programming
Docs qp example: cvxopt.org/examples/tutorial/qp.html

Another CVXOPT tutorial: courses.csail.mit.edu/6.867/wiki/images/a/a7/Qp-cvxopt.pdf

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Course Index

Course Description

The objective of this course is to give you a holistic understanding of machine learning, covering theory, application, and inner workings of supervised, unsupervised, and deep learning algorithms.

In this series, we'll be covering linear regression, K Nearest Neighbors, Support Vector Machines (SVM), flat clustering, hierarchical clustering, and neural networks.

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