Gautam-J/Machine-Learning
Implementation of different ML Algorithms from scratch, written in Python 3.x
This project helps students and aspiring data scientists understand how foundational machine learning algorithms work at a detailed level. It takes raw datasets and runs algorithms like Linear Regression, Logistic Regression, K-Nearest Neighbors, and K-Means, outputting step-by-step visualizations of their training process. It's designed for someone learning the mathematical and intuitive basis of machine learning.
410 stars. No commits in the last 6 months.
Use this if you are a student or educator who wants to visualize and deeply understand the mechanics behind core machine learning algorithms without relying on abstract library implementations.
Not ideal if you are a practitioner looking to quickly apply machine learning models to solve real-world problems or deploy them in production environments.
Stars
410
Forks
96
Language
Python
License
MIT
Category
Last pushed
Feb 01, 2024
Commits (30d)
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