StyleGAN2-ADA trained on a dataset of 2000+ sneaker images

This project is a Flask-based platform for patients, donors, and doctors, integrating hospital management in one solution. It uses Machine Learning models for predictive health analysis and Power BI for interactive dashboards. Through this project, I enhanced my skills in full-stack development, applied ML, and healthcare data solutions.

This project applies 🤖Machine Learning techniques to analyze these features and build a predictive model that estimates the selling price of diamonds

Home Loan Approval Prediction System uses machine learning to predict loan approval outcomes, helping financial institutions streamline decisions. It preprocesses data, handles missing values, encodes features, and uses a Random Forest Classifier for feature selection, optimizing the model for accuracy and efficiency.

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.

Works by building many individual decision trees and combining their outputs. For a final answer, it takes the average (for numbers) or majority vote (for categories) of all trees, making it stable and reliable.

Price comparison application using AI-ML model.

A machine learning system that predicts Netflix content popularity using Random Forest algorithms. Analyzes 8,800+ titles to forecast success based on content type, ratings, duration, and release patterns. Features interactive dashboard with 90.6% accuracy for data-driven content strategy decisions.

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

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

In this project, IPL win predictor app is created that takes user input as batting team, bowling team, host city, target score, current score, overs completed, wickets taken and returns the winning probability percentage of each team.

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.

Training model to predict passenger survival.

Also builds decision trees, but does so sequentially. Each new tree is built to specifically correct the errors made by the ones before it, allowing the model to become progressively more accurate.

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

A high-performance gradient boosting algorithm that specializes in handling categorical data (like location names or event types) directly. It excels at understanding "context" without needing complex data preprocessing.