Prototyping a Machine Learning Application with Streamlit, FastAPI, Hugging Face and Docker
Web app to predict knee osteoarthritis grade using Deep Learning and Streamlit
AgroNomics is a machine learning web application that forecasts crop prices using historical agricultural data, seasonal trends, and region-specific variables. Built with Flask and scikit-learn, it provides nationwide coverage with state- and district-level insights, enabling farmers to make accurate, data-driven market decisions.
Interactive Streamlit app that predicts house prices using multiple machine learning models. Users can adjust real-world features via sliders, compare model performance, and explore feature impact through visual insights.
🔍 Flask-based web application for image classification. The application leverages the ResNet50 model from Keras to classify uploaded images.
A movie recommendation engine that recommends you movies based on their similarity to a movie that you've already watched and liked.
A ML application focused on EDA and basketball analytics, showcasing data visualization and insights using Python and relevant libraries.
Live ML app that predicts which GP practices will overspend on NHS prescribing. Upload a raw NHSBSA file, get at-risk practices ranked by predicted overspend. Random Forest (R²=0.95) built with scikit-learn and Streamlit.
A simple mahcine learning application for stock prices, demonstrating data preprocessing, model training, and deployment using scikit-learn.
Comparative study of supervised machine learning architectures for multi-class medical classification using real-world clinical datasets.
ML Web-App using Tensorflow and Django.
Flusk Tutorial is featuring a to Flask, a Python web framework. It may include basic or tutorials covering Flask fundamentals for Machine Learning.
AgroNomics is a machine learning web application that forecasts crop prices using historical agricultural data, seasonal trends, and region-specific variables. Built with Flask and scikit-learn, it provides nationwide coverage with state- and district-level insights, enabling farmers to make accurate, data-driven market decisions.
This project predicts housing prices in Boston using machine learning techniques.
🏠 Built with machine learning, Dockerized for containerization, and automated with GitHub Actions for seamless CI/CD deployment with Render.
AI Powered Loan Approval Prediction System using Machine Learning & Streamlit
🌸 A beginner-friendly Streamlit web app that predicts Iris flower species using a Random Forest classifier. Interactive, educational, and deployed on Streamlit Cloud.
End-to-end ML web app: trains, saves, and serves a sentiment classifier via Streamlit. Python + scikit-learn.
Web App to do Sentiment Analysis on the given text
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