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Machine Learning Repository

Welcome to my Machine Learning repository! This project is a collection of implementations, datasets, and small projects focused on understanding and applying Machine Learning (ML) concepts. The repository is divided into several folders for better organization and usability.

Repository Structure

  • Algos_From_Scratch/

    • Contains implementations of various machine learning algorithms coded from scratch in Python.
    • Focused on building a deep understanding of how ML algorithms work under the hood.
    • Algorithms included (but not limited to):
      • Linear Regression
      • Logistic Regression
      • Decision Trees
      • Naive Bayes
      • K-Nearest Neighbors
      • Support Vector Machines
      • Perceptron

  • Datasets/

    • Includes datasets used for testing, training, and experimenting with ML models.

  • Small_Projects/

    • A collection of small, focused projects that demonstrate the application of ML techniques.
    • Project on Polynomial LinearRegression

  • Libraries/ -Exploratory Data analysis with Numpy,Matplotlib and Pandas

How to Use

  1. Clone the Repository: 
    git clone https://github.com/addo561/Ml-DL.git
cd ML-DL