Stanford CS229: Machine Learning Full Course taught by Andrew Ng | Autumn 2018 - 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/ai 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