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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] ⓘ