How to Train a Machine Learning Model as a REST API and Build a Spam Classifier (Part 1)

This tutorial teaches how to build a machine learning model, train it, and turn it into a REST API using Python and Visual Studio Code. The project involves creating a spam detection machine learning model from scratch and deploying it into production. Key technologies used include DataStax Astra DB for automatic connection to Cassandra and Python 3.9 or above. The tutorial guides users through setting up, preparing, and exporting datasets, training the AI Spam Classifier using LSTM model, uploading models and metadata to object storage providers like Linode and Digital Ocean, creating a reusable AI model class, configuring FastAPI app, loading Keras model and predictions, integrating with Astra DB, storing inference data on Cassandra, paginating the Cassandra model, testing the AI as an API through ngrok, and deploying the application into production.

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