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

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How to Use

1. Clone the Repository:

   git clone https://github.com/addo561/Ml-DL.git
   cd ML-DL