How to Deploy Machine Learning/Deep Learning Models To The Web

In this article, you will learn how to deploy your deep learning model as a REST API, and add a form to take the input from the user, and return the predictions from the model. We will use FastAPI to create it as an API and deploy it for free on Heroku.

The full value of your deep learning models comes from enabling others to use them. Learn how to deploy your model to the web and access it as a REST API, and begin to share the power of your machine learning development with the world If you are in the field of machine learning for some time, you must have created some machine learning or deep learning models. You must have thought about how will people use your Jupyter notebook? The answer is they won’t.

People can not use your Jupyter notebooks, and you need to deploy your model either as an API or as a complete web service, or in a mobile device, Raspberry PI, etc.

In this article, you will learn how to deploy your deep learning model as a REST API, and add a form to take the input from the user, and return the predictions from the model.

We will use FastAPI to create it as an API and deploy it for free on Heroku.

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We supply you with world class machine learning experts / ML Developers with years of domain experience who can add more value to your business.

What is the difference between machine learning and artificial intelligence and deep learning? Supervised learning is best for classification and regressions Machine Learning models. You can read more about them in this article.