Projects
Empower ITSM system with Machine Learning
Empower ITSM System with ML is an intelligent IT Service Management (ITSM) solution that leverages Machine Learning and Time Series Forecasting to improve incident handling, resource planning, and operational efficiency.
Home Loan Default Classification
This project focuses on predicting whether a home loan applicant is likely to default using machine learning. By analyzing customer demographics, financial history, and credit behavior, the model assists banks in reducing credit risk and improving loan approval accuracy.
Texas Employee Salary Predictor 💰
This project builds a predictive model to forecast monthly salaries for Texas state government employees based on various factors including agency, job classification, employment status, and demographics. The model helps the Texas state government understand compensation patterns and make data-driven decisions for payroll forecasting and budget planning.
Cell Phone Range Classification
This project focuses on predicting the price range of cell phones based on their technical specifications. Using machine learning techniques, the model classifies mobile phones into predefined price categories (0–3) based on features such as battery power, RAM, camera quality, processor speed, display characteristics, and more.
Airline Fare Estimator
Airline Flights Data Analysis & Machine Learning Project 📋 Project Overview This project focuses on analyzing airline flight data and building a machine learning model to predict flight prices based on various features such as airline, source/destination cities, departure/arrival times, duration, stops, and days left until departure.
Rice Leaf Disease Classifier
This project focuses on classifying rice leaf diseases using image processing and machine learning techniques. The model identifies various rice leaf diseases such as Brown Spot, Leaf Blast, and Narrow Brown Spot based on visual features extracted from leaf images.
PR Sentiment Analyzer (Comming Soon...)
This project analyzes the sentiment of public relations messages using natural language processing and machine learning techniques. It classifies messages as positive, negative, or neutral, helping organizations understand public perception and manage their communication strategies effectively.