🪨 Machine learning project using logistic regression to classify sonar signals as either rocks or mines. Uses scikit-learn to train a binary classifier on sonar dataset with 60 numerical features for accurate underwater object detection.

Key word/wake word detection with espressif esp32s3

Machine Learning as a Service for HEP

Seatbelt detection using YOLOv5 ML model

Fine-tuning OpenAI's Whisper model on Persian speech datasets for enhanced automatic speech recognition (ASR) performance.

Animal Classification: A CNN-based image recognition model.

Group project for Hackathon

This is an end-to-end ML project, which aims at developing a classification model for the problem of predicting credit card frauds using a given labeled dataset. The classifier used for this project is RandomForestClassifier. Deployed in Heroku.

A Machine Learning model created using prebuild model. We need to feed the images to the model and it will predict if the same person is there else it will mark as unknown.

EY Hackathon Project

Comment Toxic Analyzer build on machine Learning algorithm (Random Forest) capable to analyze toxicity present in comment or any text with the accuracy of around 83%

SugarSense : The Diabetes Prediction Application

Predict the winning team of IPL matches using XGBoost and Flask, powered by historical data from 2008–2024.

to predict the survival of the fittest.

Developed as part of the Huawei Internship Program in collaboration with Kuwait University. It replicates a simplified version of Huawei SmartCare’s churn analysis.

Forecasting the crime in a city from OSN data

An image classification machine learning model that recognizes hot dogs.

Video-based surgical skill assessment using 3D convolutional neural networks

AI-powered real estate platform with ML-based price prediction , search + filters, admin dashboard, and interactive property mapping built using Next.js, Node.js, and MongoDB.

The Smart Crop Disease Detection System is a Django web app that uses machine learning to identify crop diseases from leaf images. It helps farmers detect diseases quickly and take action to protect their crops. The system features AWS S3 image storage, TensorFlow Lite integration, and a responsive front-end for easy use.