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Numerical Methods and ML for ChE (F22-06-325)
Introduction & License
Course Info
Logistics/Notes
Course schedule
Syllabus
Software Environments
Helpful Resources
Course Notes
Recap of Numerical Methods
ODE Integration (with Events!)
More complicated example: Van der Pol oscillator
Local Optimization and Curve Fitting
Introduction to Machine Learning
Intro to Supervised Learning
Model Capacity, Overfitting, Regularization, and Ridge/LASSO
Linear models for classification
Validation and Test Splits
Non-parametric models
Featurizing molecules and materials for chemical engineering
Neural Networks
Unsupervised learning: dimensionality reduction
Design of Experiments (Active Learning) with Bayesian Optimization
Labs and Python/Software Tips
Python functions, Error handling, Exceptions, Debugging
Assignments
Course Project Overview
Predicting Wildfire Smoke Composition
Using ML to Predict Catalyst Properties
Finding optimal tours for the Travelling Salesman Problem
Homeworks
HW1 (due noon Monday 9/5)
HW2 (due 9/12)
HW3 (due 9/26)
HW4 (due Monday 10/3 noon) [100 pts]
HW5 (due Monday 10/10 noon)
Homework solutions
repository
open issue
.md
.pdf
Introduction to Machine Learning
Introduction to Machine Learning
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