Aradhya Srivastava

HeartSense: Heart Disease Prediction Web App

An end-to-end machine learning web application using Flask to predict the probability of heart disease based on patient clinical data.

• Trained and serialized a Random Forest classifier on a medical dataset
• Built a RESTful backend with Flask and interactive front-end with Bootstrap
• Achieved model accuracy of more than 85%

Sentiment Analysis Application

End-to-end NLP pipeline in Python for classifying text sentiment using NLTK, Bag-of-Words, TF-IDF vectorization, and Logistic Regression.

• Text cleaning, normalization, tokenization, stop-word removal, and lemmatization
• Integrated BoW and TF-IDF vectorization for feature extraction
• Modular pipeline separating pre-processing, vectorization, training, and prediction

FOX Assistant

A virtual assistant application developed using JavaScript to automate tasks and provide voice or text-based assistance.

• Built a Python voice assistant using SpeechRecognition and pyttsx3 for voice-based task automation.
• Implemented web search, application control, and speech synthesis through API integrations and modular command handling.
• Developed a modular, scalable architecture with exception handling for improved maintainability and extensibility.

Attendance Manager Using Flask

A web-based attendance management system built using Flask and HTML to track and manage student or employee attendance efficiently.

Bike Rental System

A comprehensive bike rental system developed in Java, enabling users to rent bikes and administrators to manage inventory.

Hospital Management System

Python-based desktop application using Tkinter to manage hospital and patient records with structured user interfaces and validated data input.

Parking Management System

A robust parking management solution built with TypeScript, designed to streamline vehicle entry, exit, and billing operations.

SnakeGame

A classic Snake Game implementation built using Python, featuring interactive gameplay and dynamic score tracking.