6.874/6.802/20.390/20.490/HST.506 Spring 2021 Prof. Manolis Kellis
Deep Learning in the Life Sciences / Computational Systems Biology
Playlist:    • MIT Deep Learning in Life Sciences - ...  
Latest slides and course today: http://compbio.mit.edu/6874
Spring 2021 slides and materials: http://mit6874.github.io/

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 generalization
1:21:20 Conclusion, Questions, Goodbyes