Machine Learn Model deployed on production using Flask API
You must have Scikit Learn, Pandas (for Machine Leraning Model) and Flask (for API) installed.
This project has four major parts :
- model.py - This contains code fot our Machine Learning model to predict employee salaries absed on trainign data in 'hiring.csv' file.
- app.py - This contains Flask APIs that receives employee details through GUI or API calls, computes the precited value based on our model and returns it.
- request.py - This uses requests module to call APIs already defined in app.py and dispalys the returned value.
- templates - This folder contains the HTML template to allow user to enter employee detail and displays the predicted employee salary.
- Ensure that you are in the project home directory. Create the machine learning model by running below command -
python model.py
This would create a serialized version of our model into a file model.pkl
- Run app.py using below command to start Flask API
python app.py
By default, flask will run on port 5000.
- Navigate to URL http://localhost:5000
You should be able to view the homepage as below :
Enter valid numerical values in all 3 input boxes and hit Predict.
If everything goes well, you should be able to see the predcited salary vaule on the HTML page!
- You can also send direct POST requests to FLask API using Python's inbuilt request module Run the beow command to send the request with some pre-popuated values -
python request.py