The code is organized in the following notebooks:

• 01-data-preparation: prepares and sample the data for fine-tuning the BERT-based model.
• 02-data-classification: performs fine-tuning of the BERT-based model for text classification, showing step by step and running locally.
• 03-data-registration: uploads the prepared and sampled data to an Azure Blob Storage location and registers it as a Dataset within Azure ML.
• 04-data-classification-aml: performs fine-tuning of the BERT-based model for text classification, using Azure ML for distributed remote training and model hyperparameter search.

Notebooks 01-data-preparation and 02-data-classification can be run independently of Azure ML.

To run notebooks 03-data-registration and 04-data-classification-aml you will need access to an Azure Subscription and an Azure ML Worspace.