DeepShot is a machine learning model designed to predict NBA game outcomes using advanced team statistics and rolling averages. It combines historical performance trends with contextual game data to deliver highly accurate win predictions (71%)

A comparative study of various models for prediction of Win/Loss of a basketball game based on the team’s as well as players’ past statistics. Also focused on the web scraping techniques to scrap raw datasets from the nba/stats website and feature engineering on the collected datasets to best suit the classification problem.

Showing an NBA Dataset through interactive visualizations.

This repository contains the projects that I made in the Python programming language.

Mini projects completed from udemy utilising Python & R Programming

Implementation of KNN, Centroid, Linear Regression and SVM classifiers using Sklearn.

Data Science Foundations I | Exploratory Data Analysis in Python | Summarizing Relationship Between Two Features