GroundUpML is a collection of fundamental machine learning algorithms implemented entirely from the ground up, without relying on high-level libraries. This repository is dedicated to helping learners and enthusiasts understand the inner workings of key ML models by diving deep into the foundational math and code behind each algorithm.
- Implementations of classic algorithms such as linear regression, decision trees, k-means clustering, and more.
- Explanations and code that break down the algorithms step-by-step.
- A focus on clarity and education, aimed at those who want to truly understand machine learning.
Whether you're a beginner looking to deepen your understanding or an experienced developer interested in revisiting core concepts, GroundUpML provides a clear and approachable way to learn machine learning from scratch!