Introduction
Deep learning is an advanced form of machine learning that tries to emulate the way the human brain learns. Increasingly, deep learning is used to build complex models that support artificial intelligence challenges like computer vision and natural language processing.
Azure Databricks is a great choice of platform for training deep learning models for multiple reasons:
- It enables you to work with the large volumes of data needed to effectively train deep learning models.
- It offers support for scalable GPU-based clusters, which provide the best performance for the kinds of matrix and vector operations that deep learning model training involves.
- Common deep learning frameworks such as PyTorch and TensorFlow are preinstalled in Azure Databricks ML clusters; as are other useful libraries such as Horovod for distributed training of deep learning models.
This module provides an introduction to some of the core principles of deep learning, with a focus on how to use PyTorch in Azure Databricks.
Tip
For a more general introduction to deep learning, we recommend you complete the Train and evaluate deep learning models module; which includes some of the same information as this module, but covers additional concepts and implementation topics in more depth.