33. Neural Nets and the Learning Function

MIT Matrix Methods in Data Analysis, Signal Processing, and Machine Learning, Spring 2018 Instructor: Gilbert Strang View the complete course: YouTube Playlist: This lecture focuses on the construction of the learning function F, which is optimized by stochastic gradient descent and applied to the training data to minimize the loss. Professor Strang also begins his review of distance matrices. License: Creative Commons BY-NC-SA More information at More courses at