Welcome back to the second part of our recommender engine tutorial series. In the first part, you learned how to train a recommender model using a variant of collaborative filtering and neural network embeddings.

In this part, you’re going to create a simple book web application that displays a set of books and also recommends new books to any selected user. Below is the end-goal of this tutorial:

Book Recommender Web app

Link to Source Code

Table of Contents

• Introducing the App Architecture
• Initializing the App and Creating Code Directories
• Converting the Saved Model to JavaScript Format
• Creating the Entry Point and Routes
• Loading the Saved Model and Making Recommendations
• Creating the UI and Displaying Recommendations
• Testing the Application

Build, Train and Deploy a Book Recommender System using Keras and TensorFlow.js, - Part 1

#keras #tensorflow