Getting started with Snap Machine Learning (Snap ML)
Find information about getting started with SNAP ML
This release of PowerAI includes Technology preview of Snap Machine Learning (Snap ML). Snap ML is a library for training generalized linear models. It is being developed at IBM® with the vision to remove training time as a bottleneck for machine learning applications. Snap ML supports a large number of classical machine learning models and scales gracefully to data sets with billions of examples and/or features. It offers distributed training, GPU acceleration and supports sparse data structures.
The Snap ML library offers three different packages:
- snap-ml-local
- snap-ml-local is used for machine learning on a single machine.
For information on snap-ml-local, see
/opt/DL/snap-ml-local/doc/README.md
- snap-ml-mpi
- snap-ml-mpi is used for distributed training of machine learning models
across a cluster of machines.
For information about snap-ml-mpi, see
/opt/DL/snap-ml-mpi/doc/README.md
- snap-ml-spark
- Similar to snap-ml-mpi, the snap-ml-spark package
offers distributed training of models across a cluster of machines. The library is exposed to the
user through a spark.ml-like interface and can seamlessly be integrated into
existing pySpark application.
For information on snap-ml-spark, see
/opt/DL/snap-ml-spark/doc/README.md