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Linear Algebra and Differential Eq.
Calculus
ManifoldBasics
Numerical Computation 4
Machine learning Basics 5
Machine learning Basics
5.1 Learning Algorithm
5.2 Capacity, Overfitting, Underfitting
5.3 Hyper-Parameters and Validation Set
5.7 Supervised Learning
5.8 Unsupervised Learning
5.9 Stocastic Gradient Decent
5.10 Building a Machine Learning Algo
5.11 Challenges Motivating Deeplearning
Inference
Deep Feedfroward networks 6
Regularization 7
Optimization for Deep-models 8
Convolutional Network 9
SpectralClustering
GAN
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Machine learning Basics 5
Machine learning Basics
5.1 Learning Algorithm
A
5.2 Capacity, Overfitting, Underfitting
A
5.3 Hyper-Parameters and Validation Set
5.7 Supervised Learning
A
5.8 Unsupervised Learning
A
5.9 Stocastic Gradient Decent
5.10 Building a Machine Learning Algo
5.11 Challenges Motivating Deeplearning
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