Lectures
Lecture Resources
Here are a few links to useful additional material for reading and viewing:
- J. Goodman’s Introduction to Fourier Optics Link
- The Matrix Cookbook Link
- An introduction to conjugate gradient descent without all the pain Link
- Online learning and stochastic approximation Link
Jupyter Notebook Examples
- Jupyter Notebook: Tensorflow basic optimization example
- Jupyter Notebook: High level intro to Neural Networks in Tensorflow
- Jupyter Notebook: Weighted image sum example - Associated cube1.mat datafile
- Jupyter Notebook: Physical layers example
- Jupyter Notebook: A simple Autoencoder in Tensorflow/Keras
- Jupyter Notebook: GAN example