Rohan Gonjari's Projects
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
This project provides a user interface to perform functions on the Automobile Insurance database. The following actions are available to users: • User can add a new accident to the database: o The user can enter the date and location of the accident, to be stored in the Accidents table. o For each automobile involved in the accident, the user can enter the information to be stored in the Involvements table. • User can find the details about a given accident: o The user can enter an accident id number. o The application will display the date and location of the accident. o For each automobile involved in the accident, the application will display the vin number, damages, and driver ssn (if applicable). • User can search for accidents meeting the user's criteria: o The user can specify any or all of the following: ▪ a range of dates ▪ a range of average damages to the automobiles involved ▪ a range of total damages to the automobiles involved o The application will display the accident id, date, and location for each accident meeting the user's search criteria.
An ongoing repository of data on coronavirus cases and deaths in the U.S.
A collection of datasets
Data Viz DSC 530 Major Project
Implementation of Conway's Game of Life. The Game of Life is a cellular automaton in which a certain set of rules were applied and the growth of the grid was observed over time. The project was implemented in Python.
Price prediction for housing properties around the King County
An attempt to solve the 2022 Data Regression Challenge where we calculate the medical score of patients
Parallel implementation of Conway's Game of Life via MPI in Python.
A short intro about me, myself and I.
Personal portfolio - https://rohang2504.github.io/
A collection of my tableau visualizations
Visualizing Olympics data from 1960 to 2016 using the D3.js framework
forceSimulation Examples
Implementing YOLO, an object detection method, using a deep learning framework to run the algorithm and detect objects.