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01 Aug 23 What is Deep Learning[Video]
02 Aug 25 Defining Learning[Video]
03 Aug 30 Intro to Probability, PAC-Learning, Linear Algebra[Video]
04 Sep 1 Finish Into to Linear Algebra - Perceptrons[Video]
05 Sep 8 Perceptron Learning[Video]
06 Sep 13 PAC-Learning Gradual Thresholds - Python[Video]
07 Sep 15 Finish Python - Go-No-Go Results for Perceptrons[Video]
08 Sep 20 Finish Perceptron Go-No-Go Results- Start SVMs[Video]
09 Sep 22 SVMs[Video]
10 Sep 27 Finish SVMs - Numpy[Video]
11 Sep 29 PIllow - Neural Net Experiments[Video]
12 Oct 4 Estimators, Multi-layer Perceptrons[Video]
13 Oct 6 MLE Cost Functions Cross Entropy[Video]
14 Oct 18 Finish Cross Entropy, Softmax Layers, Minimization Methods[Video]
15 Oct 20 Stochastic Gradient Descent, Backpropagation[Video]
16 Oct 25 Keras and Tensorflow[Video]
17 Oct 27 Training and Evaluating Keras - Regularization - Data Augmentation[Video]
18 Nov 1 More Regularization - Start Optimization[Video]
19 Nov 3 Finish Optimization[Video]
20 Nov 8 More Keras - CNNs - Start RNNs[Video]
21 Nov 10 Recurrent Neural Networks[Video]
22 Nov 15 Finish RNNs - Neural Network Tuning[Video]
23 Nov 17 NN Design Methodology[Video]
24 Nov 22 Finish NN Design - NN Applications[Video]
25 Nov 29 More NN Application[Video]
26 Dec 1 Tensorboard - GANs[Video]
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