• Overview
• Technical Aspect
• Installation
• Run
• Setup Postman
• Directory Tree
• Technologies Used

Machine Learning models are powerful tools to make predictions based on available data. To make these models useful, they need to be deployed so that other’s can easily access them through an API (application programming interface) to make predictions. A REST API that uses HTTP requests to GET, PUT, POST and DELETE data.

For this project I build simple Logistic Regreesion to predict Diabetic Patients and deploy it with Flask Framework in local host. API is accessed by Postman.

The Code is written in Python 3.7. To install the required packages and libraries, run this command in the project directory after cloning the repository:

pip install -r requirements.txt

To run use this command in you virtualenv

python app.py

To download Postman click this link

Method

Content

Body

{
  "data":{
      "Pregnancies": 6,
      "Glucose" : 148.0,
      "BloodPressure" : 72.0,
      "SkinThickness" : 35.0,
      "Insulin" : 79.79,
      "BMI" : 33.6,
      "DiabetesPedigreeFunction": 0.627,
      "Age" : 50
  }
}

Response

├── LogisticRegression 
│   ├── LogisticRegression.py
├── app.py
├── diabetes.csv
├── Logistic Regression.ipynb
├── modelForPrediction.sav
├── requiremntes.txt
├── README.md
└── standardScalar.sav