Market Overview

Software AG Launches new Open Source Library for Standards-based AI, Machine Learning and Predictive Analytics

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Software
AG
(Frankfurt TecDAX: SOW) today announced the availability of Nyoka,
an open source library that enables data scientists to transform
Artificial Intelligence (AI), Predictive Analytics and Machine Learning
models into the Predictive Model Markup Language (PMML) industry
standard. Nyoka is a Python library that provides comprehensive support
for the latest PMML standard as well as extensions for data
preprocessing, script execution and deep neural networks. Nyoka
underscores Software AG's commitment to open industry standards and
complements its Zementis
predictive analytics
for enterprise-grade, operational deployment of
AI.

Dr. Michael Zeller, Senior Vice President, AI Strategy & Innovation,
Software AG, said: "To address the challenges that organizations face
with complex AI solutions, frequent model updates, cross-platform
execution as well as data integration, Software AG emphasizes a vendor
neutral approach that provides users plug-and-play simplicity with a
wide range of components. Nyoka streamlines the work of data scientists,
reduces the complexities of deploying machine learning models, and gives
them more time to focus on creating new models that deliver increased
business value."

PMML is an XML-based predictive model interchange format and the leading
standard for statistical and data mining models. The Data Mining Group
(DMG), an independent, vendor-led consortium that develops data mining
standards, spearheaded the development of PMML for nearly twenty years
in support of the Data Science community.

Holger Mueller, VP and Principle Analyst at Constellation Research,
said: "The increasingly complex, multi-vendor IT environment, coupled
with a rapidly growing collection of open source machine learning
packages has multiplied the value of open industry standards. To truly
scale smarter, AI-driven applications across the organization, it will
be imperative to establish consistent processes that leverage open
platforms."

In its initial release, Nyoka provides a wealth of classes and functions
that are designed to make the data scientist's life easier. For example,
Nyoka enables developers to create a PMML file for a Random Forest model
from an existing scikit-learn object. Nyoka comes with an extensive HTML
documentation and a growing number of Jupyter Notebook tutorials which
demonstrate how Nyoka supports the use of PMML as a transport file
format for data science models.

With Zementis, Software AG delivers a common predictive analytics
strategy across the entire IT ecosystem. In supporting the PMML industry
standard, Zementis provides an efficient process for instant operational
deployment of models exported through Nyoka as well as many other data
science tools, thus addressing the highest execution requirements for
batch processing, in-memory computation and streaming data. Zementis is
an integral part of the Digital Business Platform and is a strategic
part of Software AG's Cumulocity IoT solution.

Nyoka will be presented for the first time at the Big
Data Conference
in Santa Clara, CA, starting today. It is available
on GitHub at https://github.com/nyoka-pmml/nyoka
and compatible with Python version 3.5+.

About Software AG

Software AG (Frankfurt TecDAX: SOW) helps companies with their digital
transformation. With Software AG's Digital Business Platform, companies
can better interact with their customers and bring them on new ‘digital'
journeys, promote unique value propositions, and create new business
opportunities. In the Internet of Things (IoT) market, Software AG
enables enterprises to integrate, connect and manage IoT components as
well as analyze data and predict future events based on Artificial
Intelligence (AI). The Digital Business Platform is built on decades of
uncompromising software development, IT experience and technological
leadership. Software AG has more than 4,500 employees, is active in 70
countries and had revenues of € 879 million in 2017. To learn more,
visit www.softwareag.com.

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