Deploy Machine Learning Model with backend(flask) and frontend(Angular) -Part2

Last time, we worked with jupyter notebook and build our machine learning model.
Today, we will make a backend and will use this ML model into our backend.

We will use flask for creating our backend.
Create a python file named ‘api.py’ which will contain a method for sending the prediction using the ML model.
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First create a virtual environment
virtualenv myenv
Actiavate virtual environment (for windows)
myenv\Scripts\activate
Install all required libraries from requirement.txt
pip install requirements.txt 

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Run the api.py file
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We are all set.
Check the localhost
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We also deployed the backend at Heroku.
If you want the full code and structure which was deployed to the server then check our git only for backend from here.

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