January 25, 2019
Industry Applications of Machine Learning and Data Science
Speaker: Ralf Klinkenberg, RapidMiner
This presentation provides an overview of industry applications of machine learning and predictive analytics in the automotive, aviation, chemical, manufacturing, pharmaceutical, steel, and other industries covering the following use cases:
- Predictive Maintenance: Predicting and Preventing Machine Failures before they happen.
- Prediction, Prevention, and Resolution of Critical Situations in Continuous Production Processes.
- Product Quality Prediction in early stages of the production process.
- Optimization of Production Processes.
- Optimization of Mixture of Materials or Ingredients.
- Assembly Time and Assembly Plan Prediction for New Product Designs.
- Demand Forecasting and Price Forecasting.
- Web Mining and Information Extraction for Semi-Automation of Price Quote Generation and Purchase Processes.
- Web Mining and Information Extraction for Market Intelligence, Trend Monitoring, and Competitive Intelligence.
- Semi-Automated Data Augmentation from Internal and External Data Sources.
These use cases cover both, industry deployments as well as new application use cases from the RapidMiner Research Lab.
Co-Founder & Head of Data Science Research, RapidMiner
Ralf Klinkenberg, co-founder of and head of data science research at RapidMiner and initiator and co-organizer of the Industrial Data Science Conference, is a data-driven entrepreneur with more than 20 years of experience in machine learning and advanced data analytics research, software development, consulting, and applications in the automotive, aviation, chemical, finance, healthcare, insurance, internet, manufacturing, pharmaceutical, retail, software, and telecom industries. In 2001 he initiated the open source data mining software project RapidMiner with Dr. Ingo Mierswa and Dr. Simon Fischer and in 2007 he founded the predictive analytics software company RapidMiner with Dr. Ingo Mierswa. In 2008 he won the European Open Source Business Award and in 2016 he was awarded the European Data Innovator Award. Since May 2017, Ralf Klinkenberg is member of the steering committee of the Platform for Learning Systems (Plattform Lernende Systeme) of the national German department for research and education (Bundesministerium für Bildung und Forschung (BMBF)), an innovation initiative of the German government via which the German government intents to promote the use of Machine Learning in industry and society. Ralf Klinkenberg is passionate about learning in humans and machines as well as about how to leverage data with machine learning and predictive analytics to make organizations more data-driven, more agile, more efficient and effective, both from a business and a technical perspective.