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SHUBH SHRISHRIMAL's Projects

car-price-predictor icon car-price-predictor

This repository contains a project aimed at predicting car prices using a Random Forest model

diabetes-detection-in-women icon diabetes-detection-in-women

A diabetes detection model uses machine learning algorithms to analyze medical data, identifying patterns to predict the likelihood of diabetes, aiding early diagnosis and effective management of the condition.

ipl-win-predictor-2024 icon ipl-win-predictor-2024

The IPL Win Predictor is designed to analyze historical match data and predict the outcome of future IPL matches. The project involves data preprocessing, feature engineering, model training, and evaluation. A Streamlit app is used for the front-end to interact with the model.

loan-approval-model icon loan-approval-model

A Streamlit-based web app for predicting loan approval using machine learning. Users input financial details, and the app assesses loan eligibility with a stacked model.

movie-recommender-system icon movie-recommender-system

This project aims to create a movie recommendation system using collaborative filtering and content-based filtering techniques

mushroom-classifier icon mushroom-classifier

Mushroom Classifier: A Streamlit-powered web app for predicting mushroom edibility using machine learning. Built with Python, Pandas, and scikit-learn.

olympic-analyser icon olympic-analyser

This project is a comprehensive analysis tool for exploring Olympic Games data, designed to provide insights into various aspects of the games through a user-friendly web interface. Built with Python, it leverages libraries such as Pandas for data manipulation

smoke-detection-model icon smoke-detection-model

Smoke detection system leverages machine learning to identify smoke in images or sensor data, providing early fire warnings through accurate, real-time analysis and classification of potential smoke events

sms-spam-detection icon sms-spam-detection

This repository contains an SMS Spam Detection Model built using machine learning techniques. The objective of this project is to classify SMS messages as either spam or ham (non-spam). By leveraging natural language processing (NLP) and various machine learning algorithms

whatsapp-chats-analyzer icon whatsapp-chats-analyzer

This project is a comprehensive WhatsApp chat analyzer built with Python, leveraging Streamlit for an interactive web app interface.

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