Training and deploying a BlazingText model

In the recipe Generating a synthetic dataset for text classification problems, we prepared the dataset we will use to train the BlazingText model. In this recipe, we will use the SageMaker Python SDK to train and deploy a BlazingText model that can be used for sentiment analysis applications.

After we have completed this recipe, we will be able to pass a sentence such as I would recommend this to my friends as the payload to an inference endpoint and get the correct classification, which is POSITIVE.

Getting ready

Here are the prerequisites for this recipe:

• This recipe continues from Generating a synthetic dataset for text classification problems.
• A SageMaker Studio notebook running the Python 3 (Data Science) kernel.

How to do it…

The first steps in this recipe focus on preparing the prerequisites for training and deploying the BlazingText model using the SageMaker Python SDK:

1. Create a new notebook...