ETL and Advanced Machine Learning - Open Source, No Code Required

Free webinar: Quick, practical introduction to KNIME Analytics Platform

KNIME Analytics Platform Workbench

Join our webinar on October 27, 2020 at 1:30 PM

Europe / Asia

October 27 at 1:30 PM - 2:30 PM UTC +1 (Berlin)

Register Now

Americas

October 27 at 1:30 PM - 2:30 PM UTC -5 (Chicago)

Register Now
Extensive extensive data prep and blending as well as vast ML capabilities in a modern data science platform that lets you leverage your experience. Open source, free, and easy to install and use.

As a data science professional, you have challenges:

  • Reducing the time needed to automate gathering and preparing data so you have time to focus on what’s important.
  • Integrating new data science methods, from simple to sophisticated such as deep learning, advanced ML, text mining, time series, and more from a single platform.
  • Extending your capabilities without requiring an up-front contractual commitment.

knime_icons_rz With KNIME, you have:

  • A modern, open source data science platform with a visual workflow editor that lets you focus on learning methods rather than learning the tool itself.
  • An extremely wide range of data sources, tools, and methods - many based on leading open source projects - all within one platform.
  • Software that is open source and free. No limitations on methods, data, or operating systems.
  • A strong KNIME community to support you, including thousands of freely available working examples.

KNIME: The Software and the Company

At KNIME, we build software for fast, easy and intuitive access to advanced data science, helping organizations drive innovation. For over a decade, a thriving community of data scientists in over 60 countries has been working with our platform on every kind of data: from numbers to images, molecules to humans, signals to complex networks, and simple statistics to big data analytics.

Register now: Quick, practical introduction to KNIME Analytics Platform

Europe / Asia

October 27 at 1:30 PM - 2:30 PM UTC +1 (Berlin)

Register Now

Americas

October 27 at 1:30 PM - 2:30 PM UTC -5 (Chicago)

Register Now