Deep Learning(CS7015): Lec 6.4 Principal Component Analysis and its Interpretations
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Deep Learning(CS7015): Lec 5.9 Gradient Descent with Adaptive Learning Rate
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Deep Learning Part - II (CS7015): Lec 17.2 Factors in Markov Network
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Deep Learning Part - II (CS7015): Lec 19.1 Markov Chains
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Deep Learning Part - II (CS7015): Lec 22.1 Generative Adversarial Networks - The Intuition
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Deep Learning(CS7015): Lec 1.3 The Deep Revival
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Deep Learning(CS7015): Lec 1.3 The Deep Revival
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Deep Learning Part - II (CS7015): Lec 19.4Training RBMs Using Gibbs Sampling
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15:24
Deep Learning Part - II (CS7015): Lec 17.3 Local Independencies in …
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Deep Learning(CS7015): Lec 1.9 (Need for) Sanity
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Deep Learning(CS7015): Lec 4.10 Information content, Entropy & cr…
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Deep Learning(CS7015): Lec 2.2 McCulloch Pitts Neuron, Threshol…
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Deep Learning(CS7015): Lec 2.3 Perceptrons
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Deep Learning(CS7015): Lec 1.1 Biological Neuron
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Deep Learning Part - II (CS7015): Lec 18.1 Joint Distributions
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Deep Learning Part - II (CS7015): Lec 18.7 Motivation for Sampling
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Deep Learning Part - II (CS7015): Lec 18.3 Restricted Boltzmann Ma…
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Deep Learning Part - II (CS7015): Lec 18.5 Unsupervised Learning w…
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Deep Learning(CS7015): Lec 1.6 The Curious Case of Sequences
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Deep Learning Part - II (CS7015): Lec 19.5 Training RBMS Using Co…
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Deep Learning Part - II (CS7015): Lec 16.10 I-Maps
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Deep Learning Part - II (CS7015): Lec 20.2 Variational Autoencoders…
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Deep Learning Part - II (CS7015): Lec 16.6 Independencies encoded …
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Deep Learning Part - II (CS7015): Lec 16.1 Why are we interested in …
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Deep Learning Part - II (CS7015): Lec 20.1 Revisiting Autoencoders
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