A free, browser-based educational platform designed to demystify high-level machine learning, calculus, and 3D geometry. We break down complex academic research into live, runnable simulations.
Mathematical formulas on a whiteboard are abstract. We use browser-based APIs to render complex calculus and linear algebra into tangible, interactive 3D simulations.
Instead of treating neural networks like black boxes, our modules dissect the underlying mathematics of generative models, enabling students to understand the 'why' behind the output.
This module leads you through the foundational concepts of calculus, from the history of its development to its applications in modern machine learning .
A deep dive into the mathematics of removing high-frequency noise from AI-generated meshes. Learn how continuous calculus (second-order derivatives) is discretized into simple arithmetic to create a functional smoothing engine.
Understand the mathematics of spatial alignment. Discover how Singular Value Decomposition (SVD) and nearest-neighbor matching snap misaligned 3D point clouds together, and explore the fatal flaw of local minima.
A deep dive into the anatomy of matrices. Learn how complex transformations are factored into Rotate-Stretch-Rotate operations, forming the mathematical bedrock for noise reduction and 3D alignment.
Mathematics means nothing if the code cannot execute. Discover the Architecture of Speed—how splitting 3D space recursively drops computational complexity from a crushing $$O(n^2)$$ down to an efficient $$O(n \log n)$$
The mathematical judge of machine learning. Explore the objective function that drives gradient descent, and discover why squaring the error is the ultimate tool for hunting outliers and optimizing AI models.