README.md

# Instruction for running

## ML-Model-Flask-Deployment
This is the code for machine learn models using flask

### Prerequisites
Scikit Learn, Pandas (for Machine Leraning Model) and Flask

### Project Structure
This project has four major parts :
1. `model.py` - contains code fot our Machine Learning model 
2. `app.py` - contains Flask APIs that receives details through GUI or API calls
3. `request.py` - uses requests module to call APIs and dispalys the returned value.
4. `templates` - This folder contains the HTML template 

### Running the project
1. Create the machine learning model 
```
python model.py
```
This creates serialized version of our model into model.pkl

2. Run app.py using below command
```
python app.py
```
Flask should run on port 5000.

3. Navigate to http://localhost:5000

You should be able to view the homepage

Enter valid numerical values in all 3 input boxes and hit Predict.

4. Can also send direct POST requests to FLask API using Python's inbuilt request module


Below command to send the request with some pre-popuated values -
```
python request.py
```