Serving large ml models independently and asynchronously via message queue and kv-storage for communication with other services [EXPERIMENT]
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Updated
Jul 20, 2021 - Python
Serving large ml models independently and asynchronously via message queue and kv-storage for communication with other services [EXPERIMENT]
A Flask web app deployed and uses built Regression model to predict an individual's likelihood to seek mental healthcare treatament.
Bangalore house prediction model + website fundamentals(with flask)
Tutorial to deploy a ML Model to Heroku with Flask web application.
[🥉 3rd place] AI-powered web application able to track changes in the urban landscape
ChurnShield – AI-powered Flask web app predicting customer churn and generating personalized retention strategies with a Random Forest ML pipeline and admin dashboard.
GreenFund is an AI-powered web application that empowers farmers to make data-driven, climate-smart agricultural decisions. The platform focuses on analysis of soil health then additionally tracks farm activities, measures carbon emissions, and provides AI-driven crop recommendations to promote sustainable and climate-resilient farming.
This is a Machine Learning + Flask Web App that predicts whether a customer is likely to churn and suggests a discount policy based on churn probability.
Machine learning–based diagnostic support system using a Random Forest model to predict heart disease and stroke, delivered via a web application (React + Flask) that provides risk predictions, basic recommendations, and downloadable health reports.
Interactive Machine Learning web app that predicts student marks from study hours using Linear Regression, with real-time training, evaluation metrics, and visualization.
ML scientific job orchestration platform: FastAPI API, Celery Worker, PostgreSQL DB, RabbitMQ broker, and React frontend for spectral analysis, Sklearn data preprocessing, and Tensorflow active‐learning workflows 🪐
ML Based Gender Predictor developed in Flask and Material Design bootstrap
ML web app predicting diabetes likelihood from patient health indicators. Trains a scikit-learn classifier, serialises it to model.pkl, and serves predictions through a Flask interface. Educational project — not a medical device.
📊 Regression Model Selection Web App | Compare Multiple ML Models 🚀 An interactive Machine Learning web app that trains and compares multiple regression models (Linear, Polynomial, Random Forest, Decision Tree, SVR) and automatically selects the best model based on R² score. Built with Python, Scikit-learn & Streamlit.
Used car price prediction web app using Gradient Boosting. Takes fuel type, transmission, mileage and ownership as inputs. Built with Flask and Scikit-learn.
🩺 Diabetes Prediction App using Deep Learning | Streamlit Web App 🚀 An interactive Machine Learning application that predicts diabetes based on medical inputs using an Artificial Neural Network (Keras & TensorFlow). Features real-time prediction, user-friendly UI, and healthcare-focused insights.
ML web app estimating house prices from property features. Trains a scikit-learn regression model, persists it as model.pkl, and serves predictions through Flask — a complete train, persist, serve pipeline.
A simple machine learning web-based app using flask python
Flight ticket price prediction (Random Forest) with a Flask web app. B.Tech final-year project, published in IJSREM 2024.
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