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Machine Learning Notebooks

Overview

This repository contains Jupyter notebooks developed during the process of learning core Machine Learning concepts and algorithms. Each notebook demonstrates practical applications, code, and notes from study sessions.

Contents

  • Supervised_ML: Notebooks on supervised learning topics.
  • Unsupervised_ML: Notebooks on unsupervised learning topics.

Usage

Feel free to browse the folders and open notebooks in Jupyter or Google Colab. All notebooks use standard Python machine learning libraries.

Purpose

Created as personal study notes to document hands-on exploration of machine learning topics and techniques. Useful for students and practitioners who want to review, test, or build upon core ML workflows.


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A personal collection of Jupyter notebooks created while learning machine learning. Includes practical examples, code, and notes on supervised and unsupervised algorithms to support hands-on learning and experimentation.

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