This is a flask based app for Diabetes Prediction, which provide the website as well as API feature. In this used 'Pima Indian Diabetes Dataset' to build the machine learning model.

Learn keras with two simple examples

This repo related to the analysis of pima-indian-diabetes dataset

A RESTful API using Flask and XGBoost to predict diabetes in Pima Indians based on various diagnostic measurements. Includes training, saving the best model, and testing the API using Python requests.

Diabetes Prediction using Decision Tree Algorithm - Machine Learning Project - Pima Indians Diabetes Database - Jupyter Notebook - Python

Using various supervised learning estimators in Sci-Kit Learn to get the best prediction accuracy if possible for the pima indians dataset.

A multi-layer perceptron which predicts whether an individual is susceptible to diabetes

In this project we are removing the outliers before doing the classification. This is done for a research paper purpose for our Research Methodologies exam course

Machine Learning Exercise: Using Logistic Regression, Naive Bayes and Random Forest to classify people with and without diabetes based on Pima Indian data from Kaggle

Implement a feedforward neural network for Pima Indians onset of diabetes dataset using TensorFlow & Keras

This project explores and compares two diabetes-related datasets using data preprocessing, visualization, and machine learning models. It includes performance evaluation of classifiers like Logistic Regression and Random Forest to identify key factors influencing diabetes risk and improve prediction accuracy.

In this project, different machine learning approaches are used to detect the diabetes in patients using the PIMA Indians diabetes dataset.

Pima Diabetes Outcome

🩺 AI-powered Diabetes Detection System using Random Forest Classifier, Flask API, and a cyber-themed medical dashboard UI built with Chart.js

Pima-Indian Diabetes Classification

Predictive modeling project for early diabetes detection using the Pima Indians dataset. Includes EDA, statistical testing, and Random Forest classification.

Pima Indians Dataset classification using Tensorflow Linear Classifier and DNN Classifier.

Build a machine learning model to accurately predict whether or not the patients in the dataset have diabetes or not?

To explore the given dataset for all basic statistics such as the distributions, correlations, outliers, missing values, etc.