This project focuses on predicting the market values of
football players using machine learning techniques. By analyzing various player
performance statistics such as age, goals, dribbling, and reputation, the system
provides estimates of their market worth. The project includes both server-side and
client-side implementations, with a Flask-based RESTful API for the server and web and
mobile interfaces for the client.
click here for github repo
This project involves building a house price
prediction model for Mumbai using data from Kaggle. The process includes data
exploration and cleaning, feature engineering, and model selection (Linear Regression,
Random Forest, Decision Tree) with hyperparameter tuning. The Random Forest Regressor
performed the best. The final trained model is saved as a pickle file for easy
predictions
click here for github repo
Sparkyy has different fun commands,anime commands,meme
commands,supercell game commands etc.
click here for github repo
Created this 2d game which has the same concept
that
we have played when we were young.Wasn't able to put much time into this as i had
other
deadlines too(lol)
click here for github repo
This is created using HTML,Bootstrap CSS, JavaScript and
Rapid-Api.
Made this as I wanted to learn how to fetch data from an API in
javascript
click here for github repo