Machine Learning

Project Overview

A collection of machine learning projects that apply various techniques like classification, regression, clustering, and text analysis to real-world problems.

Machine learning covers a wide range of techniques. There was a need to showcase proficiency in different ML areas and demonstrate how these techniques can solve real-world problems.

Developed a series of projects, each focusing on a different ML aspect. These include spam detection, heart disease prediction, and happiness score analysis, showing practical problem-solving in ML.

Features

• Advanced spam detection using SVM and text preprocessing
• Heart disease prediction with multiple classifiers and ensemble methods
• Linear regression on World Happiness Report data to predict scores
• Iris species prediction with Random Forest and K-Means clustering
• Comprehensive model evaluation with metrics and visualizations

Project Gallery