Analytics Insight

10 Machine Learning Projects for Beginners to Advanced (2026)

Overview: Machine learning skills improve when concepts are applied through regular, structured, hands-on projects.Working on projects across text, images, and ...
IEEE

Analysis of spam detection techniques using machine learning

Abstract: In recent years, the receipt of spam by billions of users around the world has increased. In general, for spam emails are admitted all emails that is sent without the express consent of the ...
IEEE

Enhancing Machine Learning Algorithms for Imbalanced Data—A Case Study: Spam Detection

Abstract: Nowadays, emails are among the most common and cost-effective ways to share and exchange information. However, because of their simplicity, they are highly vulnerable to various threats. In ...
GitHub

Machine Learning spam classifier achieving 98% accuracy using SVM, NLP, and TF-IDF vectorization

An intelligent spam detection system that classifies SMS/email messages with 98.48% accuracy using machine learning. This project compares multiple algorithms and provides comprehensive performance ...
ahajournals.org

Abstract Fri013: AI-Driven Gait Classification for Peripheral Artery Disease (PAD) Detection Using Machine Learning and Nonlinear Gait Dynamics

Introduction: Peripheral Artery Disease (PAD) is a progressive vascular disorder impairing mobility, raising fall risk, and reducing quality of life. Early detection is key to preventing amputations ...
C&EN

Using Response Surface Methodology To Enhance Limited Data Sets for Machine Learning: A Polyvinyl Butyral Synthesis-Based Chemistry Undergraduate Teaching Case

School of Chemical Engineering and Light Industry, Guangdong University of Technology, Guangzhou, 510006, China ...
GitHub

MusXIII/SMS_SPAM_DETECTION

This project implements a machine learning model to classify SMS messages as "spam" or "ham" (not spam) using Decision Trees and TF-IDF vectorization. CS_Project_II/ ├── dataset/ │ └── spam.csv # SMS ...