Blogs

Python Numpy Tutorial

python, numpy, scipy, matplotlib

K Nearest Neighbor

splits strategy, L1/L2 Distances, hyperparameter search, cross validation

Linear Classification

svm, softmax, parameteric approach, bias trick, hinge loss, cross entropy loss, L2 regularization

Optimization

sgd, optimization landscapes, random search, learning rate, gradient check

Backpropagation

chain rule, computation graph, patterns in gradient flow

Neural Networks - Setting Up The Architecture

biological neuron, activation functions, neural net architecture, representational power

Neural Networks - Setting Up The Data And The Loss

preprocessing, weight initialization, batch normalization, regularization, loss functions

Neural Networks - Learning And Evaluation

gradient checks, sanity checks, babysitting, momentum, newton methods, adagrad, rmsprop, hyperparameter optimization, model ensembles

Minimal Neural Network

generating data, softmax linear classifier, initialize parameters, class scores, loss, analytic gradient, backpropagation, parameter update, Neural Network

Implement Batch Normalization

computational graph

Convolutional Neural Networks

architectures, convolution, pooling, spatial arrangement, layer pattern, Alex/ZF/VGG, computational consideration

Understanding And Visualizing Convolutional Neural Networks

tSNE embeddings, deconvolution, Occluding, Saliency Maps, data gradients, fooling ConvNets, human comparisons

Transfer Learning And Fine Tuning Convolutional Neural Networks

read more

Understanding Reinforcement Learning

Markov Decision Processes, Policies, Value Functions, Bellman Equations