illustrated-machine-learning/machine-learning-from-scratch
This repository contains the implementation from scratch of some of the most used Machine Learning algorithms
This project provides the underlying code for popular machine learning algorithms, written from the ground up. It takes basic data and applies common machine learning methods to show how they work, step-by-step. This is for students, educators, or anyone looking to understand the fundamental mechanics behind machine learning without relying on high-level libraries.
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Use this if you want to gain a deeper, hands-on understanding of how core machine learning algorithms like K-Means or Logistic Regression function internally.
Not ideal if you need to quickly apply machine learning models to real-world problems or develop production-ready applications.
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Python
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Last pushed
Jan 30, 2023
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