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A collection of fundamental machine learning algorithms implemented from the ground up using pure Python (NumPy, Pandas, etc.), without relying on high-level ML libraries like Scikit-learn or TensorFlow.

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prem-ramamoorthy/ML-Implementation

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ML-Implementation

Welcome to ML-From-Scratch, a comprehensive collection of fundamental machine learning algorithms meticulously implemented from the ground up using pure Python. This repository avoids the use of high-level machine learning libraries like Scikit-learn or TensorFlow, focusing instead on building a deep understanding of the core concepts and mathematics behind these algorithms.

Key Features:

  • Hands-on Learning: Gain insights into how machine learning algorithms work under the hood.
  • Pure Python Implementation: Built using foundational libraries like NumPy and Pandas for maximum transparency.
  • Educational Focus: Ideal for students, educators, and enthusiasts looking to strengthen their grasp of machine learning fundamentals.

Dive in and start exploring the building blocks of machine learning!

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A collection of fundamental machine learning algorithms implemented from the ground up using pure Python (NumPy, Pandas, etc.), without relying on high-level ML libraries like Scikit-learn or TensorFlow.

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