CS undergrad at Marwadi University, specializing in Machine Learning, I'm actively working on innovative projects and enhancing my skills through Competitive Coding on LeetCode.
Made with:
Developed a Tesla Stock price prediction model using data from January 1, 2020, to January 1, 2023, covering 1,096 days. Achieved an R² score of 0.95 and MSE of 10.5 on the training set, and an R² score of 0.93 and MSE of 12.3 on the test set.
Made with:
This project focuses on leveraging machine learning to analyze a chronic kidney disease dataset. It encompasses data preprocessing, feature engineering, and model development to predict patient outcomes. The goal is to create a robust predictive model that aids in early diagnosis and enhances decision-making for chronic kidney disease management.
Made with:
This Movie Recommendation System project utilizes the MovieLens dataset to predict user ratings for movies based on their genre features. By employing a deep neural network with multiple dense and dropout layers, the model effectively captures complex relationships between movie genres and user preferences.
Made with:
ENIGMA is a sophisticated travel planning solution that leverages advanced algorithms to deliver tailored itineraries and dynamic recommendations. Designed for efficiency and ease of use, it integrates real-time updates and seamless synchronization with popular tools, ensuring a streamlined and personalized travel experience.
Made with:
Developed a comprehensive calorie tracker using Django, this application empowers users to monitor their daily caloric intake efficiently. It features user authentication, a robust database for food items, and detailed logging capabilities. The application allows users to add, track, and analyze their food consumption, providing insights into their nutritional habits through an intuitive and responsive interface..
Made with:
Developed a hate speech detection system using natural language processing and machine learning. This tool classifies tweets into "Hate speech," "Not offensive," or "Neutral" by employing a Decision Tree Classifier combined with custom text preprocessing techniques. It features a user-friendly interface for real-time classification and feedback, enhancing online content moderation and promoting a safer digital environment.
Made with:
Console app that manages tasks in a project. Users can load projects from a file and generate a seqeuence to complete them in, based on each task's dependencies. Users can also find earliest possible commencement time of each task, add new tasks, update tasks, remove tasks, and save the results to a text file.
Made with:
Python program that implements a breadth-first search algorithm to generate a minimal spanning tree. Problem was to calculate a shortest path from a starting vertex in a graph to each other vertex. The vertices represent people and each person is related to every other person through parent-child relationships. A person can see how they are related to each other person in the tree.