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LynnFernandes23 / repository
The Diabetes Prediction System is a comprehensive web application utilizing HTML for the frontend and Python's Flask framework for the backend. It leverages Pandas and NumPy for efficient data management, employing Scikit-Learn to develop robust machine learning models. Matplotlib is used for insightful data visualization.
The Diabetes Prediction System is a comprehensive web application utilizing HTML for the frontend and Python's Flask framework for the backend. It leverages Pandas and NumPy for efficient data management, employing Scikit-Learn to develop robust machine learning models. Matplotlib is used for insightful data visualization.The system guarantees precise predictions of diabetes outcomes by rigorously preprocessing data and employing a variety of machine learning algorithms. Users access the system through an intuitive HTML interface, facilitating easy interaction and quick access to prediction results. This project demonstrates proficiency in full-stack development, seamless integration of machine learning capabilities, and effective application of data visualization techniques for predictive analytics.
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shreyrai99 /
A website for making accurate predictions of whether a patient has Diabetes or not using machine learning. Implemented the machine learning models using the sklearn library. Used HTML and CSS for frontend and Flask for the backend of the website.
tejasbhirud /
This is a Diabetes Prediction Web Application. I have done Analysis of the project using Python, Machine Learning. I also used Flask which is a web application framework written in Python. The Web Application where it shows the output using HTML, CSS, Bootstrap. I am sharing the source code along with the dataset I used for the project.
Ranjan2104 /
It is a Model that Predict the Diabetes Status of any person by just giving the some observations so that take the decision on that with the accuracy of 93%+. Due to Trained Model with Data sets so that able to predict very carefully on the previous decision it is supervised learning model using an algorithm is Linear regression and Sklearn for testing and Training the Model and Flask is Uses in Backend and in Frontend HTML, CSS, Js is Using.
GxAniket /
A Flask web app that predicts the risk of diabetes based on user input using a trained machine learning model. Built with scikit-learn, pandas, and HTML/CSS. Simple UI, real-time predictions, and easy to deploy. Ideal for learning ML model deployment in web applications.
aurelioo29 /
Repository diabetes prediction application built with Flask and machine learning models. It predicts the likelihood of diabetes based on user inputs, providing a simple and efficient solution for early detection.
hossain-sanowar /
Developed a Diabetes testing model utilizing Machine Learning Algorithms, the Flask API for Web Applications, and the Heroku cloud infrastructure.