Skip to article frontmatterSkip to article content
Site not loading correctly?

This may be due to an incorrect BASE_URL configuration. See the MyST Documentation for reference.

Scientific Machine Learning

Data, Inference, and Scientific ML | COMP 521

San Diego State University

Purpose

This unit treats machine learning as a scientific modeling task: define a target, choose and inspect features, evaluate generalization, and explain what the model can and cannot support.

Reading sequence

  1. Supervised learning from scratch

  2. Clustering, PCA, and model evaluation

The module builds on the course’s earlier habits: make assumptions explicit, test failure modes, and do not mistake a score for a scientific conclusion.

Model Fitting and Uncertainty (in preparation)
Model Fitting and Uncertainty
Scientific Machine Learning (in preparation)
Supervised Learning from Scratch