KNIME Analytics Platform 4.0 is now available!

We’ve just released the latest versions of KNIME Analytics Platform and KNIME Server. Here’s a quick summary of what’s new.

With KNIME Analytics Platform 4.0, there are many new features that allow easier sharing with the community, as well as a tighter integration with the new KNIME Hub.

Speaking of which... with this release, we’ve got a bunch of exciting new features. Share workflows and components publicly on the KNIME Hub, browse KNIME extensions, drag and drop nodes into your KNIME workbench, and search the KNIME Hub from within KNIME Analytics Platform.

KNIME Spring Summit 2019, Berlin: Summary

From March 18-22 we held our 12th annual KNIME Spring Summit in Berlin, Germany. KNIME users and enthusiasts got together for a week of courses, presentations, workshops, an evening at the movies, and the chance to network. This year we welcomed over 400 people through the doors. Alongside the regular Summit attendees, it was great to see so many new faces. Thank you to everyone who joined us!

KNIME Analytics Platform 3.7 is now available!

We’ve just released the latest versions of KNIME Analytics Platform and KNIME Server and here’s a quick summary of what’s new.

Some of the highlights in this release are a number of new interactive views (check out the new Tile View* and Heatmap), new integrations allowing KNIME workflows direct access to Google Drive and Tableau’s Hyper format, and a number of new statistical tests. New XGBoost nodes add access to this well known high performance machine library, while a more hidden gem is the completely new layout editor for composite views of metanodes, which allows you to build your own library of personalized view nodes.

KNIME at AWS re:Invent Helping Machine Learning Builders

Amazon Web Services re:Invent is taking place on November 26 -30, 2018 in Las Vegas, NV and KNIME will be there! This conference offers machine learning “Builder Sessions” and an “AWS Marketplace Machine Learning Hub” including KNIME Software. The goal of these hands-on sessions is to provide attendees expert guidance on machine learning building and data science automation for predictive quality management, predicting risk, and predicting excess stock inventory models.

NEW: KNIME Publishes ML Models in AWS Marketplace for Machine Learning

The new AWS Marketplace for Machine Learning lists KNIME workflow models ready to deploy to Amazon SageMaker. The KNIME models provide AWS Marketplace customers self-service, on-demand deployment for faster execution. KNIME workflow models are deployed as Docker containers for automated Amazon SageMaker delivery.