The Apache SystemML team is pleased to announce the release of Apache
SystemML version 0.9.0-incubating. This is the first release as an Apache
project.

Apache SystemML provides declarative large-scale machine learning (ML) that
aims at flexible specification of ML algorithms and automatic generation of
hybrid runtime plans ranging from single-node, in-memory computations, to
distributed computations on Apache Hadoop MapReduce and Apache Spark.

Extensive updates have been made to the release in several areas. These
include APIs, data ingestion, optimizations, language and runtime
operators, new algorithms, testing, and online documentation.

*APIs*

Improvements to MLContext and to MLPipeline wrappers

*Data Ingestion*

Data conversion utilities (from RDDs and DataFrames)
Data transformations on raw data sets

*Optimizations*

Extensions to compilation chain, including IPA
Improvements to parfor
Improved execution of concurrent Spark jobs
New rewrites, including eager RDD caching and repartitioning
Improvements to buffer pool caching
Partitioning-preserving operations
On-demand creation of SparkContext
Efficient use of RDD checkpointing

*Language and Runtime Operators*

New matrix multiplication operators (e.g., ZipMM)
New multi-threaded readers and operators
Extended aggregation-outer operations for different relational operators
Sample capability

*New Algorithms*

Alternating Least Squares (Conjugate Gradient)
Cubic Splines (Conjugate Gradient and Direct Solve)

*Testing*

PyDML algorithm tests
Test suite refactoring
Improvements to performance tests

*Online Documentation*

GitHub README
Quick Start Guide
DML and PyDML Programming Guide
MLContext Programming Guide
Algorithms Reference
DML Language Reference
Debugger Guide


To download the distribution, please go to :

http://systemml.apache.org/

The Apache SystemML Team

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Apache SystemML is an effort undergoing Incubation
<https://incubator.apache.org/index.html> at The Apache Software Foundation
(ASF), sponsored by the Incubator. Incubation is required of all newly
accepted projects until a further review indicates that the infrastructure,
communications, and decision making process have stabilized in a manner
consistent with other successful ASF projects. While incubation status is
not necessarily a reflection of the completeness or stability of the code,
it does indicate that the project has yet to be fully endorsed by the ASF.

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