PCA 5: Feature selection and feature extraction

Neural Networks 1: a 3-minute history

Neural Networks 2: machine learning = feature engineering

Neural Networks 3: axons, dendrites, synapses

Neural Networks 4: McCulloch & Pitts neuron

Neural Networks 5: feedforward, recurrent and RBM

Neural Networks 6: solving XOR with a hidden layer

Neural Networks 7: universal approximation

Neural Networks 8: hidden units = features

Neural Networks 9: derivatives we need for backprop

Backpropagation: how it works

Neural Networks 11: Backpropagation in detail

Neural Networks 12: multiclass classification