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There are a set of steps to follow in order to deploy an app onto the Heroku Platform:
1. Make a web interface for our model:
It is quite obvious that we should be having an app, for us it host it publicly :P.
So to host a machine learning or deep learning model, the first step is to train a model.
Then, we create a web interface, often using frameworks like Django or Flask, and make the app and web-app.
We have already done all this in the project How to Deploy an Image Classification Model using Flask.
2. Create the requirements.txt file:
requirements.txt file is where we mention the details of all the packages - along with their corresponding versions - which are used in the project.
This is a very important step in every real-case scenario because the app runs smoothly only if its dependencies are correctly installed.
Similarly, Heroku relies on this
requirements.txt file to install the dependencies and makes all the necessary arrangements to host the app.
3. Make the Procfile:
Procfile is like a configuration file to our app.
It mentions to Heroku the entry-point for the app.
Hence we shall define this file.
4. Commit the code on Git and push it to GitHub:
GitHub is a version-control platform to host the source codes of our projects.
To host our app on Heroku, we link our project directory - along with the
requirements.txt - which we push to GitHub.
5. Signup on Heroku Platform and Setting up Heroku::
We need to create an account on Heroku.
Once we log-in, we choose the option to link the GitHub repository to Heroku.
Heroku then provides us the option to deploy(either automatically or manually). It installs the necessary dependencies as per the
requirements.txt and sets all the configurations as per the
After Heroku does all such background work to host our app, it provides the link to the app.
We could browse through that link and use our app.
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