Lecture 7 – Kernels | Stanford CS229: Machine Learning Andrew Ng (Autumn 2018)

For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/3GftN16

Andrew Ng
Adjunct Professor of Computer Science
https://www.andrewng.org/

To follow along with the course schedule and syllabus, visit:
http://cs229.stanford.edu/syllabus-autumn2018.html

0:00 Introduction
0:10 Support vector machine algorithm
2:47 Derivation of this classification problem
7:47 Decision boundary
11:58 The represented theorem
13:20 Logistic Regression
26:31 The dual optimization problem
28:48 Apply kernels
28:56 Kernel trick
31:45 A kernel function
33:56 No free lunch theorem
34:40 Example of kernels
54:13 Kernel matrix
59:16 Gaussian kernel
59:39 The gaussian kernel
1:11:57 Dual form
1:13:35 Examples of SVM kernels
1:14:13 Handwritten digit classification
1:15:39 Protein sequence classifier
1:17:03 Design a feature vector

source