Altair RapidMiner Studio 10.2 and Altair AI Hub 10.2
are now available to all licensed users, and we recommend that all customer
organizations plan their upgrades now.
Click here to read the release notes and other
documentation for RapidMiner
Studio — and here for documentation on RapidMiner
AI Hub.
Please
contact our support team here if you have any questions about the upgrade or
need any technical assistance.
Learn more about
the Altair RapidMiner platform here.
This short video provides an overview of the changes
in this new release:
https://rapidminer.wistia.com/medias/huw3o6j0ip<br></div>
Here are highlights of this release:
- Interactive decision trees: Decision trees are highly explainable and allow people, even those
without data science backgrounds, to visualize complex interactions within data
and understand exactly how an AI model produces its output. Altair RapidMiner
Studio now provides business users, data scientists, and analysts with a
wizard-based tool for building Altair’s unique, patented decision trees that
they can incorporate into their AI models. Users can grow trees automatically,
find the best splits, delete splits, and save scoring workflows they can then
deploy using Altair RapidMiner AI Hub. Decision trees built in Altair
RapidMiner Studio are based on the same technology implemented in Altair
Knowledge Studio. Note: Activating the interactive decision
tree feature results in a draw of 10 additional Altair Units.
- Spark 3 support in Radoop: The Radoop extension for Altair RapidMiner Studio provides a graphical interface for
analyzing data on Hadoop clusters. This release supports Spark 3, making it
fully compatible with Java 11 and Altair RapidMiner 10.x, and including all
existing capabilities related to push-down execution in Spark.
- Scalable and user-friendly
web APIs: Using Altair RapidMiner AI Hub, users can
now expose workflows built in Altair RapidMiner Studio as scalable and secure
web API (that is, REST) endpoints easily through the web interface of AI Hub.
They can deploy endpoints to load-balanced groups of web API agents and trigger
updates of deployments manually or automatically. This greatly simplifies the
deployment process and improves scalability and security for AI models built in
Altair RapidMiner Studio and deployed on RapidMiner AI Hub.
- Other important changes: This release ships a language pack for Japanese and Chinese (note
that we do not yet have translated version of the documentation). RapidMiner AI
Hub now allows users to clean up project histories manually or automatically. Users
can also create Panopticon dashboards that display the output of RapidMiner workflows.
Training
RapidMiner
Academy offers bite-sized learning along with curated
courses and pathways, designed to match roles, knowledge domains, and skill
levels. Everything in RapidMiner Academy is self-paced, and free — including
our certification program. Check out the Get Started
with RapidMiner and Machine Learning path for an introduction to
RapidMiner Studio, as well as important data science concepts.
We also host live, interactive training
sessions about the Altair RapidMiner platform every month.
Click here for details.
