Lecture
Before Mid
Lecture 1 - KNN and Regression
Lecture 2 - Naive Bayes, Feature Reduction
Lecture 3 - Ensemble Learning
Lecture 4 - Optimizers, Hyperparameter Tuning
Lecture 5 - CNN
Lecture 6 - CNN Cont
After Mid
Lecture 7 - Transfer Learning & Auto Encoders
Lecture 8 - Speech and RNNs
Expanded Explanations
Lecture 1 Examples
Lecture 2 Examples
Lecture 3
Lecture 4 Examples
Lecture 5
Supervised/Expanded Explanations/Lecture 7