Ansh Gandhi | Projects

Movie Recommeder

(UNDER CONSTRUCTION) Developing a movie recommendation web app which allows users to browse and select movies, providing them with suggestions from a machine learning backend.

Details

Developing a dynamic React front end for users to select a movie and receive personalized recommendations
Building a machine learning back end in Python using Flask to analyze movie data and generate personalized recommendations based on user input
Integrating RESTful APIs for seamless communication and real-time recommendations

Chatting Web Application

Developed a chat application that enables real-time messaging where users can join chat rooms, send messages, and view message history.

Details

Developed a dynamic, real-time chat application using HTML, CSS, and JavaScript for the frontend
Implemented a robust back end using Node.js, Express.js, and WebSockets to handle real-time messaging and user interactions efficiently
Integrated RESTful APIs for user authentication, chat room creation, and message history and MongoDB for data storage

Stock Trend Prediction

Developed a web application to visualize actual stock price trends over time versus predicted prices.

Details

Developed a web application using Streamlit to visualize actual stock price trends over time versus predicted prices, while incorporating 100-day and 200-day moving averages for a deeper analysis
Built and trained a Long Short-Term Memory (LSTM) network, using Scikit-learn and Keras in python, for predicting stock prices, using sequential data to improve prediction accuracy
Designed intuitive, data-driven visualizations with Matplotlib and incorporated interactive trend graphs into the web app to enhance the user experience

Nom Appetit

Developed a social restaurant tracking mobile app, focusing on creating shareable lists and implementing a machine-learning algorithm for the restaurant recommendation feature.

Details

Designed and implemented a user-friendly front-end using Typescript and React Native which allows users to make seamless dining decisions
Utilized Firebase and Express to enable auto-population and import functionalities for restaurant lists with advanced sorting and commenting functionalities

Graph Abstract Data Type

Developed a graph interface and applied it to address real-world challenges, including assessing the impact of sea level rise and creating a boggle-playing bot.

Details

Implemented an adjacency matrix and adjacency list graph representation in Java to model sea levels across divserse terrains in order to predict the impact of seal level rise for city planners
Applied Dijkstra's algorithm to efficiently compute the shortest path between two nodes on the graph
Utilized JUnit testing to ensure full confidence in all the code by testing all edge cases and achieving 100% line and branch coverage

Concurrent Server

Developed a program to simulate IoT networks and create a simple concurrent server.

Details

Devloped the server to handle multiple concurrent clients utilizing Java's socket class to interact between them
Implemented a filtering mechanism that sifts through events to ensure only relevent events are passed to the client
Utilized JUnit testing to ensure full confidence in all the code by testing all edge cases and achieving 100% line and branch coverage

Epilog

Led the design of a user centric mHealth app, simplifying epilepsy management for individuals and caregivers through streamlined tasks.

Details

Coded the front-end of the reminders page and linked it to the back end using React Native, JavaScript, and Firebase
Led the design and created the logo for the app

RISC Machine

Designed and developed a microprocessor that performs a small number of computer instructions.

Details

Designed a 16-Bit instruction supported CPU on a FPGA utilizing Verilog, Quartus, and ModelSim
Created tests achieving 100% coverage ensuring correctness of the created computer instructions

Simon Game

Developed a digital simulation of an electronic game designed to challenge short-term memory skills through the memorization of sequences of flashing colors.

Details

Developed an interactive memory game using HTML, CSS, and JavaScript