Core Guides & Projects
Mathematical Foundations in Python
Hands-on explanations of manifold learning concepts with Python implementations and experiments.
Explore Repository →Manifold Learning Overview (5 Episodes)
Concise YouTube series covering intuition, algorithms, and practical tips for manifold learning.
Watch Playlist →INRIA Grenoble-Alpes Manifold Learning Course
Graduate-level course material featuring lectures, slides, and exercises on manifold learning theory.
View Course →Drexel ML & Data Analysis – Manifold Learning
Applied perspective on manifold learning within a broader machine learning curriculum.
Visit Module →Manifold learning: an informal introduction
Felix Dietrich — February 3, 2019. Notes overviewing core manifold learning ideas and algorithms.
Read Notes →Manifold learning: what, how, and why
Marina Meila & Hanyu Zhang — November 8, 2023. Concise PDF notes summarising key manifold learning concepts.
Read Notes →Machine Learning & Algebraic Geometry
Vahid Shahverdi — March 2023. Notes connecting algebraic geometry tools with machine learning ideas.
Read Notes →Laplace–Beltrami Operator
Stanford CS233 Geometry Processing Notes
Detailed derivation of the Laplace–Beltrami operator with geometric processing applications.
Read Notes →CMU Differential Geometry – Lecture 18
Insights into the Laplace operator from a discrete differential geometry viewpoint.
Download PDF →Laplace–Beltrami Operator Explained
Visual walkthrough of the Laplace–Beltrami operator, intuition, and applications.
Watch Video →Colab Notebooks
BatON – Week 1 (11 Oct 2025)
Working notes and experiments from the first week’s follow-up session.
Open in Colab →BatON – Week 1 Customised (18 Oct 2025)
Extended notebook with customised workflows and additional commentary.
Open in Colab →BatON – Week 8: Chopped Torus ML Algorithms Comparison
Comparative study of manifold learning algorithms on a chopped torus dataset.
Open in Colab →BatON – Week 8: Repeated Eigendirection Problem (REP)
Notebook exploring the repeated eigendirection problem and mitigation strategies.
Open in Colab →Reference Books
do Carmo – Differential Geometry of Curves and Surfaces
Classic text covering differential geometry foundations critical for understanding manifolds.
Access PDF →John M. Lee – Introduction to Smooth Manifolds
Definitive reference on smooth manifolds, coordinate charts, and tensor calculus.
Access PDF →Reinhard Diestel – Graph Theory
Comprehensive treatment of graph theory to support research on manifold connectivity and structure.
Access PDF →Algebraic Geometry and Statistical Learning Theory — Sumio Watanabe
Links algebraic geometry with statistical learning theory to explain model complexity and generalisation.
Access PDF →