Welcome to the Machine Learning Algorithms repository! This repository houses Python files that demonstrate the implementation of various machine learning algorithms. Whether you're a beginner looking to understand the basics or an experienced practitioner exploring different techniques, you'll find valuable resources here.
Algorithms Included as: Principal Component Analysis (PCA): Explore dimensionality reduction techniques using PCA.
K-means Clustering: Understand unsupervised clustering with the K-means algorithm.
Agglomerative Hierarchical Clustering (AHC): Dive into hierarchical clustering methods.
K-nearest Neighbors (KNN): Learn about instance-based classification using KNN.
Usage Each algorithm is provided in a separate Python file along with comments explaining the code and its functionality. You can clone this repository to your local machine and run the files to see these algorithms in action. Feel free to explore, experiment, and adapt these algorithms to your specific use cases. We encourage contributions and improvements from the open-source community.
Getting Started To get started, clone this repository to your local machine using the following command: git clone https://github.com/your-username/Machine-Learning-Algorithms.git Navigate to the specific algorithm's file you're interested in and run it using a Python interpreter. Don't forget to install any necessary libraries if you haven't already.