Lecture #1 History of CNN

Lecture #2 KNN & Linear Models

Lecture #3 Loss Functions & Optimization

Lecture #4 Backpropagation & the Jacobian Matrix

Lecture #5 Convolution, Stride, Padding & Layers

Lecture #6 Activation Functions & Training

Lecture #7 Normalization, Optimizers & Regularization

Lecture #8 Hardware & Deep Learning Software

Lecture #9 CNN Architectures

Lecture #10 RNN - LSTM

Lecture #11 Detection and Segmentation

Lecture #12 CNN Visualization & Interpretation

Lecture #13 Generative Model (Unsupervised Learning)