Neural Nets and Deep Learning Lec 8: Gradient Decent for Logistic Regression
Lectures 1-7 contain general introduction consisting of linear algebra, statistics and Binary classification and are not presented on the channel. The discussion of Neural Networks start from lecture 8. Viewers are requested to start from lecture 8 and then progress sequentially to gain understanding of subject.
This is lecture 8 of Neural network and Deep learning Course offered during Spring 2020 at UMT. This lecture takes logistic regression as a tiny neural network and provides intuitive explanation of Gradient decent for optimizing weights of logistic regression.
