Deploy Machine Learning models to production

Deploy Machine Learning models to production

0% completed
1 Concepts | 17 Learners

The purpose of this project is to show how to deploy your machine learning models to production. In this project, we'll train the MNIST model, save the model to the file, load the model from the file in the flask app and predict the digit for the new images. Since input images in MNIST are 28x28 greyscale images, the images used for predictions have to be processed. They should be converted to greyscale and resized to 28x28 pixels. Because of this, you may not get the accuracy in predictions but you will learn how to move your model to production (and which is the sole objective of this project).

We'll use Flask for exposing the model using the REST API for predictions. Flask is a micro web framework written in Python. It's lightweight and easy to learn.

Attempted by