Machine learning approach to detect whether patien has the diabetes or not. Data cleaning, visualization, modeling and cross validation applied

Diabetes Prediction is my weekend practice project. In this I used KNN Neighbors Classifier to trained model that is used to predict the positive or negative result. Given set of inputs are BMI(Body Mass Index),BP(Blood Pressure),Glucose Level,Insulin Level based on this features it predict whether you have diabetes or not.

Diabetes predictions application with gui

A Flask web app to predict diabetes in a patient using the SVM ML model

In this case, we train our model with several medical informations such as the blood glucose level, insulin level of patients along with whether the person has diabetes or not so this act as labels whether that person is diabetic or non-diabetic so this will be label for this case.

Diabetic classification based on retinal images

This project uses a Machine learning approach to detect whether the patient has diabetes or not using different machine learning algorithms.

Diabetes Prediction System using support vector classifier and its deployment on local machine

In the beginning, the algorithm chooses k centroids in the dataset randomly after shuffling the data. Then it calculates the distance of each point to each centroid using the euclidean distance calculation method.

In this case, we train our model with several medical informations such as the blood glucose level, insulin level of patients along with whether the person has diabetes or not so this act as labels whether that person is diabetic or non-diabetic so this will be label for this case.

This repository is a working bench on Bangkit 2022 Capstone Project for Diabetes Detection

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

Includes my work done in the field of ML especially in the medical domain

Diabetes Detection using Machine Learning Techniques

This project focuses on predicting the likelihood of diabetes in individuals using logistic regression, a powerful machine learning algorithm. Additionally, we have developed a user-friendly web application that allows users to input relevant health metrics and receive instant predictions regarding their risk of diabetes.

Machine Learning based Diabetes Detection

Machine Learning model trained to predict the possiblity of diabetes with Flask as a backend framework.