You must have Scikit Learn, Pandas (for Machine Leraning Model) and Flask (for API) installed.
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model.py - This contains code for our Machine Learning model to perform stock predictions based on the past training data in 'BTC-USD.csv', etc... files from yahoo finance for quick prototyping.
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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.
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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, eth_model, etc...
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
CHOOSE STOCK YOU WOULD LIKE TO PREDICT :
Next, WE PAY FOR THE STOCK WE WOULD LIKE TO PREDICT:
AFTERWARDS, THE STOCK PREDICTION WILL BE OUTPUTTED AFTER PAYMENT!
THE FINAL OUTPUT IS THE HEROKU HOST : https://presa-app.herokuapp.com/