Support Vector Machines are a very popular type of machine learning model used for classification when you have a small dataset. We’ll go through when to use them, how they work, and build our own using numpy. This is part of Week 1 of The Math of Intelligence. This is a re-recorded version of a video I just released a day ago (the audio/video quality is better in this one)
Code for this video:
https://github.com/llSourcell/Classifying_Data_Using_a_Support_Vector_Machine
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Course Syllabus:
https://github.com/llSourcell/The_Math_of_Intelligence
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More Learning resources:
https://www.analyticsvidhya.com/blog/2015/10/understaing-support-vector-machine-example-code/
http://www.robots.ox.ac.uk/~az/lectures/ml/lect2.pdf
http://machinelearningmastery.com/support-vector-machines-for-machine-learning/
http://www.cs.columbia.edu/~kathy/cs4701/documents/jason_svm_tutorial.pdf
http://www.statsoft.com/Textbook/Support-Vector-Machines
https://www.youtube.com/watch?v=_PwhiWxHK8o
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