There are obviously some easier ways to do it that I’m going to explain in my blog. We use Heroku and Github to deploy our model on the web.

What will we look at with this Article?

1.Using the model that you coded and built from scratch to make the app.

2. How to integrate the google model to make the app.

3. Deploying both these methods on your local machine.

5.Push the model to Github and Deploy on Heroku

Why Flask?

When I reached this stage I thought about deploying the model on GitHub pages first. GitHub Pages is a free static site hosting service designed to host projects from a GitHub Repository.

When working with web applications, I could not use GitHub Pages to host them. GitHub Pages is only meant for static websites not for something dynamic like a web application that requires a server and a database. You would have to use Cloud Services such as Amazon Web Services to link with Gitpages. So flask was the next choice since it uses **Python as a Server Side Language **and indeed integrated beautifully with the model. I learned that I could use the framework called Flask to use Python as the Server-Side Language

#artificial-intelligence #computer-vision #heroku #machine-learning #application-development