Machine-Learning-Algorithms

This repository contains a collection of Machine Learning algorithms implemented in Python. It serves as a hands-on resource for learning and practicing ML concepts with practical examples.

🔑 Key Features

• Implementation of supervised algorithms:

  • Support Vector Machine (SVM)
  • K-Nearest Neighbors (KNN)
  • Decision Trees
  • Logistic Regression
  • Linear Regression

• Implementation of unsupervised algorithms:

  • K-Means Clustering
  • Hierarchical Clustering
  • PCA (Principal Component Analysis)

• Data preprocessing using Pandas and NumPy

• Visualization of data and results using Matplotlib and Plotly

• Step-by-step workflow for each algorithm:

  • Data creation/loading
  • Feature engineering
  • Model training
  • Prediction
  • Evaluation