01Foundations
Introduction to Machine Learning
What does it mean to learn from data? Discover the core ideas, the training process, and the applications and challenges of machine learning.
Learning from dataClassificationApplications
CV7001 · Scientific Computational Methods
Machine
Learning.
From data to insight.
Explore how models learn from examples. Build your understanding through lecture notes, visual explanations, and interactive slides.
Explore the chaptersA model learns a patternIllustration
Instructor Bryan G. Pantoja-RoseroMaterials Lecture notes & slides
The course collection
Learn one chapter at a time.
Start with the foundations, then build on them.
02Prediction
Regression
Connect numerical inputs to predictions. Explore linear models, represent datasets, and understand what it means to fit a model to observations.
Linear modelsParameter fittingInterpretation
03Learning objectives
Loss Functions
Measure prediction errors and compare models. Explore how the choice of loss shapes learning, sensitivity to outliers, and the ease of optimization.
MSE & MAEOutliersConvexity
More chapters to come
Additional course materials will appear here as they become available.
Put your learning into practice
Machine Learning Mini-Project
Choose a problem that matters to you, develop and evaluate a model, and document your findings. Start with the project brief, then use the LaTeX template to prepare your report.
01 · Instructions · PDF
Project brief
The project objectives, required work, and submission instructions.
02 · Report preview · PDF
Report template
Preview the report structure and formatting before you begin writing.
03 · Editable source · LaTeX
LaTeX source
Download the editable template to use in Overleaf or your local LaTeX editor.
About this collection
A companion to your learning.
These materials cover the machine learning component of CV7001 — Scientific Computational Methods, with connections to scientific and engineering problems.
Use the lecture notes for detailed explanations and mathematical development. Open the slides for a visual overview and interactive examples. Begin with Chapter 1 and continue through the collection at your own pace.