alaha999.github.io

Course Content

We plan to have 8 sessions to cover the materials offered in this modular course. We may have a guest lecture in the last session.

Week 1: Basic math of a neural network, Basic python,numpy,pandas
Week 2: Simple regression neural network, testing it and benchmarking performance
Week 3: Simple classification, train/test splits and ROC curves
Week 4: Advanced classification task, Ranking of input variables
Week 5: Convolutional neural networks
Week 6: Examples of unsupervised learning algorithms (clustering)
Week 7: Autoencoders, and generative adversarial networks
Week 8: continue previous discussion and assessment
Week 9: continue previous discussion and assessment
Last Session:(For Week8 and Week9, we may have a guest lecture)

https://github.com/alaha999/MLPhyCourse

We expect you to have basic knowledge on python, pandas, numpy, and matplotlib
we will revisit these items and brush up in the first session.
Please check out the following link of basic tutorials on them,
- matplotlib: tutorial