Sure, I can help you with that. Here's the corrected markdown:

Diabetes Prediction Web App with Streamlit

This repository contains a simple web application for predicting diabetes using a pre-trained decision tree model. The app is built with Streamlit and allows users to input various health-related parameters through sliders, obtaining a prediction based on the trained model.

Getting Started

Prerequisites

• Python 3.6 or later
• pip (package installer for Python)

Installation

1. Clone the repository:

   git clone https://github.com/tu_usuario/tu_repositorio.git
   cd tu_repositorio

Usage

Run the Streamlit app locally:

streamlit run streamlit.py

Visit http://localhost:8501 in your web browser to interact with the application.

Input Features

The following health parameters can be adjusted using sliders:

• Number of Pregnancies
• Level of Glucose
• Level of Blood Pressure
• Skin Thickness
• Level of Insulin
• BMI (Body Mass Index)
• Diabetes Pedigree
• Age

After adjusting the sliders, click the "Predict" button to obtain a prediction on whether the user is likely to suffer from diabetes or not. The result will be displayed on the web page.

Model Details

The prediction is made using a decision tree model trained on a dataset related to diabetes. The pre-trained model is loaded from the file models/decision_tree_optimized_model.pk. The data information is taken form the X_train.csv contained in the data/processed directory.

Contributing

Feel free to contribute to this project by opening issues or submitting pull requests. Your feedback and contributions are highly appreciated.

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Happy coding :) !