Welcome to Math 452ΒΆ
This is the online companion to Math452.
contents
- Module 0 Get started: course information and preparations:
- Module 1: Linear machine learning models
- Module 2: Probability and training algorithms
- Module 3: Deep neural networks
- Nonlinear models
- Polynomials and Weierstrass theorem
- Finite element method
- Deep neural network functions
- Universal approximation properties
- Application to data classification
- DNN for image classification
- Monte Carlo Methods
- Building and Training Deep Neural Networks (DNNs) with Pytorch
- Homework 3
- Week 3 Programming Assignment
- Quiz 3
- Module 4: Convolutional neural networks
- Module 5: Normalization, ResNet and Multigrid
- Module 6: MgNet