Databricks supports deep learning libraries for building and applying neural networks. This section gives examples to get started with deep learning in Databricks using several popular libraries. We provide installation instructions as well as accompanying example notebooks to get started.
Graphics processing units (GPUs) are increasingly popular because they can accelerate deep learning and other machine learning tasks. For more information about creating GPU-enabled clusters, see GPU-enabled clusters. Databricks includes pre-installed GPU hardware drivers and NVIDIA libraries such as CUDA.
You can install TensorFlow, MXNet, and Keras as a Databricks library from PyPI. For all other deep learning libraries, we recommend that you use Init Scripts to install required libraries on clusters upon creation. We provide init scripts for those libraries.
- Deep Learning Pipelines
- Distributed Deep Learning
- Integrating Deep Learning Libraries with Apache Spark