Video Link (Click Lect. #) Date Topics
0 18 August 2020 Introduction (PDF)
1 20 August 2020 Overview of Machine Learning and Imaging (PDF)
2 20 August 2020 Continuous Mathematics Review (PDF)
3 25 August 2020 From Continuous to Discrete Mathematics (PDF)
4 27 August 2020 Discrete Functions (PDF)
5 1 September 2020 Introduction to Optimization (PDF)
6 3 September 2020 Ingredients for Machine Learning (PDF)
7 8 September 2020 Ingredients for Machine Learning, Part II (PDF)
8 10 September 2020 Linear and Logistic Classification (PDF)
9 15 September 2020 “Deep” Networks: theoretical motivation (PDF)
10 17 September 2020 Convolutional Neural Networks (PDF)
11 22 September 2020 Convolutional Neural Networks (PDF)
12 24 September 2020 Automatic Differentiation and Backpropagation (PDF)
13 29 September 2020 Tools for your Deep Learning Toolbox (PDF)
14 1 October 2020 CNN implementation details (PDF)
15 6 October 2020 CNN visualization tools and extensions (PDF)
16 8 October 2020 CNN extensions and object detection (PDF)
17 13 October 2020 Introduction to Physical Layers in Machine Learning (PDF)
18 15 October 2020 CNNs, Autoencoders and Segmentation (PDF)
19 20 October 2020 Introduction to Fourier Optics (PDF)
20 22 October 2020 Coherent Physical Layers and Layer Guidelines (PDF)
21 27 October 2020 Published Physical CNN Examples and Ethics (PDF)
22 29 October 2020 Recurrent Neural Networks (PDF)
23 5 November 2020 Generative Models (PDF)
24 10 November 2020 Reinforcement Learning (PDF)
25 12 November 2020 Machine Learning + Imaging Review (PDF)

Lecture Resources

Here are a few links to useful additional material for reading and viewing:

  1. J. Goodman’s Introduction to Fourier Optics Link
  2. The Matrix Cookbook Link
  3. An introduction to conjugate gradient descent without all the pain Link

Jupyter Notebook Examples

  1. Jupyter Notebook: Tensorflow basic optimization example
  2. Jupyter Notebook: High level intro to Neural Networks in Tensorflow
  3. Jupyter Notebook: A simple Autoencoder in Tensorflow/Keras
  4. Jupyter Notebook: Weighted image sum example - Associated cube1.mat datafile
  5. Jupyter Notebook: Physical layers example
  6. Jupyter Notebook: GAN example