Body Area Network (BAN) This repository implements a machine learning model for anomaly detection in body sensor data collected through a Body Area Network (BAN). The model analyzes heart rate and body temperature readings to identify potential health concerns.

Quantifying Integrity in the Digital Age Misinformation spreads rapidly, accountability often falters, and the lines between transparency and manipulation blur

Fertilizer prediction Api (https://predict-fertilizer-api.onrender.com/predict)

Deploy a machine-learning web app that makes predictions based on data using Python and Flask.

Sentiment Analysis For Restaurant Reviews

This project aims to detect fraudulent credit card transactions using a machine learning model. The application is built using Flask for the backend and a simple HTML form for the frontend. The model predicts fraud based on the Time and Amount features of the transaction.

This repository contains a machine learning model built to detect fake news articles. The project leverages natural language processing techniques and a supervised learning approach to classify news articles as either real or fake based on their content.

Predict Creditworthiness: Determine if a customer meets the credit underwriting criteria of LendingClub.com.

Training model to predict passenger survival.

Problem Statement: Financial institutions face significant challenges in detecting fraudulent activities due to the large volume of transactions and the sophistication of modern fraud techniques. The problem is to design AI models that can accurately detect fraudulent transactions in real-time while minimizing false positives.