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Numerical Methods and Machine Learning for Chemical Engineering

Lecture 1 - Python for Numerical Methods: the (very basic) essentials
Lecture 2 — Nonlinear systems - Root finding
Lecture 3 — Optimization (Unconstrained & Constrained)
Lecture 4 — Ordinary Differential Equations (ODEs)
Lecture 4/5 (continued) — Ordinary Differential Equations (ODEs)
Lecture 6 - Introduction to Machine Learning (ML I)
Lecture 7 — Machine Learning II, Regression: Neural Networks
Lecture 8 — Machine Learning II, Regression: Gaussian Processes
Lecture 9 — Machine Learning III, Introduction to Classification
Lecture 10 — Advanced topics I
Final Class — Advanced Topics II - Clustering, Scientific ML (PINNs & Neural ODEs) concepts, and Course Review
Group Projects - 06-325 Numerical Methods and Machine Learning for Chemical Engineering
Optimization of an Alkylation Process
Optimization of an Evaporation Process
Machine Learning Modeling of a Steam Methane Reforming Process
Machine Learning Modeling of Concrete Compressive Strength

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By Victor Alves