Chirag Radhakrishna's Projects
An interactive chatbot using the OpenAI API.
Development of Steam Engine using OpenGL library functions.
🗝️ Implementation of famous cryptography algorithms over computer networks. 🔐🔑
This repository constitutes the solutions for the weekly programming assignments as part of CSEN 233 Computer Networks taught by Professor Sin Yaw Wang at Santa Clara University.
This repository constitutes the solutions for the weekly programming assignments as part of CSEN 240 Machine Learning offered by Dr. Yen Kuang Chen at Santa Clara University.
Code to study the different parameters for random network models including degree distribution, clustering coeffecient and path length. Part of CSEN 354: Social Networks Analysis & Risks taught by Dr. Xiang Li at Santa Clara University.
Developed a project to demonstrate web application-penetration testing.
Implementation of search techniques, sorting algorithms, arrays, linked list, stack, queues and trees using Java and BlueJ.
Implementation of data structures using Python.
Mini project regarding database management as part of the curriculum prescribed by VTU.
Webpage to implement the dice game challenge
Development of a face-mask detector using tensorflow library.
Implementation of the FIB data structure for a router network. ❌
ML model for heart disease prediction
Analysis IPL match data using Python libraries.
Instruction Set Architecture and pipeline to implement a new operation in the computer hardware. Submitted the proposal as part of the project description for CSEN 210 taught by Professor Ramzi Nofal at Santa Clara University.
Development of mobile application "ReciCheese" using Android Studio IDE.
Facilitates disease prediction by diagnosing user symptoms.
An application that allows the user to book NBA tickets to the All-Star games. The application demonstrates the concept of database connectivity.
Implementation of different search algorithms for the Pacman game.
Pacman games with multi agents. Evaluating the performance of Pacman and the ghosts.
Implementing reinforcement learning for an agent and crawler. Both learn by exploring different paths to reach the goal state. Ultimately, both are able to find optimal paths. We can try both manual paths or simulate a number of episodes.
Natural Language Toolkit and Random Forest Classifier to analyze customer reviews.
Temperature Data with Node.js
Developing a command-line, GUI and web-application of a ToDoList.
Web Application for virtual drums. Clicking a drum generates respective sound.
Streamlit web-app for a weather forecast predictor using Python.
Developed a basic personal website using HTML and CSS.