Final Year Project on Road Accident Prediction using user's Location,weather conditions by applying machine Learning concepts.

A machine learning web application use to predict chances of heart disease, built with FLASK and deployed on Heroku.

Analysis and classification using machine learning algorithms on the UCI Default of Credit Card Clients Dataset.

Predict and prevent customer churn in the telecom industry with our advanced analytics and Machine Learning project. Uncover key factors driving churn and gain valuable insights into customer behavior with interactive Power BI visualizations. Empower your decision-making process with data-driven strategies and improve customer retention.

Predict Diabetes using Machine Learning and deployment of machine learning model using Django.

This is an End-to-End Data Science project which can predict whether a person has diabetes, or not, based on information about the patient such as blood pressure, body mass index (BMI), age, etc.

AI-powered healthcare platform for digitizing prescriptions, predicting diseases, and comparing medicine prices. Includes a smart chatbot, doctor matching, and emergency alert features.

In an era marked by global security challenges, the "TAFRAS" emerges as a cutting-edge solution to tackle the ever-evolving threat of terrorism. The project is grounded in the urgent need for predictive systems that can anticipate, assess, and mitigate potential terrorist activities.

Predicting Hepatocellular Carcinoma through Supervised Machine Learning

Flask backend application for generating output of pickle ML model

In this project we compute the susceptibility map o an area on the south of Como lake thanks to the Random Forest algorithm

An AI-powered web application that predicts optimal seed parameters (size, sowing depth, spacing) for different crops in Maharashtra, India, based on regional and environmental conditions.

Context: Customer behavior prediction to retain customers

A Microsoft Azure Web App project named "Covid 19 Predictor" using Machine learning Model (Random Forest Classifier Model ) that helps the user to identify whether someone is showing positive Covid symptoms or not by simply inputting certain values like oxygen level , breath rate , age, Vaccination done or not etc. with the help of kaggle database.

lighting-invariant soybean disease detection final project for the Ohio State University Computer Vision course

Proyectos de Machine Learning con SPSS Modeler

Wine reviews used to determine the type of wine training on imbalanced data using classification algorithms like SVM, Naive Bayes and Random Forest Classifier. Neural Network (CNN, RNN and LSTM) and LLM models (DistilBERT and RoBERTa) were also used followed by error analysis using SHAP.

Problem: Many Farmers are facing loses due to unstable changes in crop prices in future. So we came up with an ML Predictive model.

Transfer files through the air with just a gesture. Push. Pull. Done.