Live-Veranstaltung vor Ort
Beyond the AI Hype: Practical Machine Learning for Scientists and Engineers
Jenseits des KI-Hypes: Machine Learning in der Praxis für Wissenschaft und Technik
12. November, 15:00-17:30, Spittelmarkt, Berlin
Artificial intelligence may dominate the headlines, but scientists and engineers face a different challenge: applying machine learning to solve real-world industrial problems in process industries such as biotech, semiconductor, pharmaceuticals and chemicals.
In this seminar, discover how machine learning and advanced analytics can help you uncover patterns in complex data, build more accurate predictive models, and make better decisions throughout research, development, and manufacturing. Through practical examples from R&D, manufacturing, and process improvement, we explore how these methods complement traditional statistical approaches and where they deliver the greatest value.
Whether you're taking your first steps into machine learning or looking to expand your analytical toolkit, you'll leave with a better understanding of today's methods, their practical applications, and how they can help you solve complex scientific and engineering challenges.
Join us for an afternoon of learning, discussion, and networking with fellow scientists and engineers.
Kurz zusammengefasst: Erfahren Sie anhand praxisnaher Beispiele, wie Machine Learning und moderne Analysemethoden in Forschung, Entwicklung und Produktion eingesetzt werden können – von der Erkennung komplexer Datenmuster bis hin zu präziseren Vorhersagemodellen und besseren Entscheidungen.
Agenda:
| Time | Topic | Presenter |
| 15:00 | Registration & networking | |
| 15:20 | Welcome and Introduction |
Marcel Brüske, JMP Angelina Moncelli, JMP |
| 15:30 |
Machine Learning for Scientists and Engineers
|
Christian Zollner, JMP Astrid Ruck, JMP |
| 16:15 | Coffee Break | |
| 16:30 |
Advanced Analytics and Optimization with JMP Pro This session explores practical approaches to solving complex industrial challenges, including Bayesian optimization for efficient experimentation, complemented by one of the following advanced topics:
|
Christian Zollner, JMP Astrid Ruck, JMP |
| 17:15 | Q&A and closing |
Marcel Brüske, JMP Angelina Moncelli, JMP |
| 17:30 | Networking and refreshments |