Deep Learning in Life Sciences - Lecture 02 - Machine Learning Foundations (Spring 2021)

Spring 2021 Prof. Manolis Kellis Deep Learning in the Life Sciences / Computational Systems Biology Playlist: Latest slides and course today: Spring 2021 slides and materials: 0:00 Lecture overview 1:15 What is machine learning? 4:50 Machine learning notation and terminology 14:24 Types of machine learning 18:45 Objective functions 27:08 Optimizing the objective function 29:40 Training, validation, and test sets 35:24 Performance measures for classification: confusion matrix, ROC 39:50 Performance measures for regression: Pearson, Spearman 42:22 Significance tests 46:12 Multiple hypothesis 48:23 Correlation is not causation 52:30 Traditional neural networks 57:20 Non-linearity 1:02:07 Training a neural network: back-propagation, gradient-based learning 1:13:30 Controlling model complexity 1:14:57 Model capacity 1:15:35 Generalizability 1:19:30 Improving