Diabetes Predictor using Machine Learning.

This project is an end-to-end machine learning project that predicts whether a patient has diabetes or not based on medical report inputs. It utilizes the Support Vector Machine (SVM) algorithm from the scikit-learn library to create the predictive model.

By providing the model with relevant medical report inputs, it can predict whether a patient is likely to have diabetes or not.

Dataset: The dataset used for this project contains a set of features such as glucose level, blood pressure, insulin level, BMI, age, etc., along with a binary target variable indicating the presence or absence of diabetes.

Additionally, you need to install the following libraries: scikit-learn, numpy, pandas.

You can install these libraries using pip: bash Copy code: pip install scikit-learn numpy pandas Usage: To use this project, follow these steps:

Copy code: git clone https://github.com/your-username/your-repository.git Navigate to the project directory: bash

Copy code: cd your-repository

Run the main script: bash

Copy code: python main.py

INPUTS:

Pregnancies : Glucose : BloodPressure : Skin Thickness : Insulin : BMI : DiabetesPedigreeFunction : Age :

Improving the model's accuracy Adding new features to the dataset Optimizing the code for better performance

To contribute, fork this repository, make your changes, and submit a pull request.