Wisdom 2020 Presentations

RapidMiner’s own Head of Data Science Martin Schmitz gives an overview of the new Python Operating Framework in this presentation.

This presentation shows the latest advances in RapidMiner that will make it even easier for teams to work together towards the same goal with AI and ML.

Heatherly Carlson explores the relationship between the player intangibles and whether they have ever taken their team to a playoff game.

This session is a demonstration of the RapidMiner-Tableau Integration component developed by Bhupendra Patil of RapidMiner for classification and association mining.

Jeremy Osinski and Todd Marlin of Ernst and Young discuss how machine learning can help understand and predict employees’ and stakeholders’ intentions.

Michael Stansky of FirstEnergy demonstrates how to use RapidMiner to forecast customer contact center call volume using historical all volume and considering call volume drivers.

In this two-part presentation, Lionel demonstrates how to use clustering for preprocessing and how to use clustering for semi-supervised learning.

This presentation reviews the latest enhancements to the book, now published in its fourth edition as an interactive, smart textbook on the MyEducator platform.

In this demonstration, Rodrigo explains a proof of concept architecture used to score HTTP requests, detect attackers and block them using RapidMiner Real-Time Scoring.

Dr. Mierswa presents a manifesto for data science, a set of basic principles designed to guide our work and make sure that our models have the desired impact.

Muddasir Hassan of Anblicks discusses using artificial intelligence and IoT technology to speed up the fault detection process and predict defects faster.

Brandon Shockley of 160over90 describes the agency’s data-mining journey, from early prototypes to actionable consumer insights.

Brian Meagher of Shorelight Education talks about how Shorelight has used data science to help fuel growth and help students succeed.

This panel brings together different perspectives to discuss how they can best work collaboratively to ensure data science projects have the desired impact.

In this presentation, Gisa demonstrates her brand new extension that creates a code-free method of taking a process and wrapping it into an extension.

Ryan Frederick of Dominos talks about how his data science team worked through a complex time series forecasting exercise and scaled R-based time models.

This presentation discusses the current position of RapidMiner as a tool for personalized medicine and the new era of personalized medicine, genomics, etc.

In this session, Tamilla Triantoro presents how she adopted RapidMiner for teaching machine learning concepts, including topics and techniques she covered in class, student feedback, and the support she received from RapidMiner unicorns.

This presentation demonstrates a new extension that adds the ability for data scientists to make their projects as easily understood as possible.

This session outlines how to use RapidMiner to support investment & maintenance decision-making for linear and networked assets such as pipelines, roads, electric transmission lines, water distribution systems, etc.

Elise Watson of Clarkston Consulting shows how to use RapidMiner to enhance the health care professional’s journey.

Mahesh Vinayagam of qBotica discusses the changing landscape of the automation ecosystem, and how enterprises can best use these changes to increase efficiency.