Before revision:  Applying machine learning models to these tasks requires us to create numerical representations of the changes, i. e. embeddings. Recent studies demonstrate that the best way to obtain these embeddings is to pre-train a deep neural network in an unsupervised manner on a large volume of unlabeled data and then further fine-tune it for a specific task.
After revision:  Applying machine learning to tasks that operate with code changes requires their numerical representation.