Deep Learning(CS7015): Lec 3.4 Learning Parameters: Gradient Descent

Deep Learning Part - II (CS7015): Lec 22.1 Generative Adversarial Networks - The IntuitionSee more

Deep Learning Part - II (CS7015): Lec 20.2 Variational Autoencoders: The Neural Network PerspectiveSee more

Deep Learning(CS7015): Lec 4.6 Backpropagation: Computing Gradients w.r.t. Hidden UnitsSee more

Deep Learning(CS7015): Lec 5.9 Gradient Descent with Adaptive Learning RateSee more

Deep Learning Part - II (CS7015): Lec 19.4Training RBMs Using Gibbs SamplingSee more

Deep Learning(CS7015): Lec 5.1 & Lec 5.2 Recap: Learning Parameters: Guess Work, Gradient DescentSee more

Deep Learning Part - II (CS7015): Lec 18.6 Computing the gradient of the log likelihoodSee more

Deep Learning(CS7015): Lec 10.4 Continuous bag of words modelSee more

Deep Learning(CS7015): Lec 4.4 Backpropagation (Intuition)See more

Deep Learning(CS7015): Lec 3.1 Sigmoid NeuronSee more

Deep Learning(CS7015): Lec 4.2 Learning Paramters of Feedforward Neural Networks (Intuition)See more

Deep Learning(CS7015): Lec 8.1 Bias and VarianceSee more

Deep Learning(CS7015): Lec 5.4 Momentum based Gradient DescentSee more

Deep Learning(CS7015): Lec 14.3 How LSTMs avoid the problem of vanishing gradientsSee more

Deep Learning(CS7015): Lec 4.5 Backpropagation: Computing Gradients w.r.t. the Output UnitsSee more

Deep Learning(CS7015): Lec 2.2 McCulloch Pitts Neuron, Thresholding LogicSee more

Deep Learning(CS7015): Lec 5.3 Contours MapsSee more

Deep Learning(CS7015): Lec 13.3 Backpropagation through timeSee more

Deep Learning(CS7015): Lec 5.7 Tips for Adjusting Learning Rate and MomentumSee more