score-prediction

KitcheNette: Predicting and Recommending Food Ingredient Pairings using Siamese Neural Networks

Code for ReviewRobot: Explainable Paper Review Generation based on Knowledge Synthesis

A machine learning project that predicts the winner of Pakistan Super League (PSL) matches using historical data. It includes data preprocessing, exploratory analysis, and model training using Random Forest , achieving high accuracy in predicting match outcomes.

A prediction system for VALORANT eSports matches, more specifically, Americas Stage 1 of the VALORANT Champions Tour 2025.

Welcome to the "T20 Match Score Predictor" project! This machine learning model, built using the XGBoost regressor, predicts the final score of a T20 cricket match. Get ready to make data-driven score predictions!

Working on a simple linear regression model for predicting students' exam scores. Using a dataset with features like study time, family size, and parental backgrounds. This work is for personal training and educational purposes.

IPL First Innings prediction using python.

🏏 IPL Score Predictor – Real-time first-innings batting score forecasting web app using Lasso Regression. Predict final score based on teams, venue, current runs/wickets, overs, and recent performance. Built with Streamlit.

A Linear Regression model that predicts student exam scores based on study hours, featuring exploratory data analysis, model evaluation metrics, and an interactive Streamlit web app for real-time predictions.

This project predicts a student's Mental Health Score (0–10) based on social media usage, academic performance, daily habits, and lifestyle factors.

Using Machine Learning Models to predict IPL (20 over cricket) scores

In this project I have created an men's t20 internationals cricket score predictor considering various factors like batting team, bowling team, current score etc. and got an 99% r2 score on training and 98% r2 score on testing.

AI-powered learning platform with chatbot, file analysis, OCR, and data analytics.

This is a web application that predicts the first innings score for an IPL match based on the venue, batting team, and bowling team.

Code for the paper: "Automatic Evaluation Metrics for Artificially Generated Scientific Research" (https://arxiv.org/abs/2503.05712)

Context-aware IPL first-innings score projection engine using hybrid collapse-aware ML routing

The T20 Totalitarian project aims to leverage machine learning to predict the total score of a team in a T20 World Cup cricket match. By utilizing the powerful XGBoost algorithm, we aim to provide accurate predictions that can help in strategizing and understanding match dynamics better.