- Deployed at - https://bank-na.herokuapp.com/apidocs
- Click the above link to go to the deployed website
A basic web app deployed at heroku, which classifies whether a note is fake or not based on certain parameters, using supervised machine learning algorithms.
The Parameters/Columns Used in the dataset are.
This project is implemented end-to-end and is deployed at heroku, you can click the link above or click here to visit the web app.
-
create a virtual environment and install requirements.txt file.
-
After completing the above steps run the file main.py in your terminal.
-
After running main.py you will get an url(eg- http://127.0.0.1:5000/) copy this URl and paste it to your browser.
-
At the end of the URL add apidocs/ eg-(http://127.0.0.1:5000/apidocs) and then press enter.
-
Your flask application is now up and running and should look something like this.
. -
Click on GET Method and you will see a form something like this.
. -
Click on Try it Out and enter the values in the form as shown in the figure and after entering the values click on Execute
. -
After clicking on execute you will get a result as shown in the figure.
. -
Similarly you can also upload a csv file in this format, and get predictions for multiple records, to do so click on the post method and it will appear as shown in the figure.
. -
Upload the csv and click on execute.
-
After clicking on execute you will get the following result.
.
- For model training go to the Training Directory, and go through the notebook.