Thomas Fraunholz
Meet Thomas, a passionate advocate for science, particularly in the realm of applied mathematics. Following his doctoral studies, he embarked on a journey into the world of embedded programming, where his affinity for DevOps took root. His enduring passion for crunching numbers ultimately led him to the fascinating field of artificial intelligence, where he's now an acknowledged MLOps expert, seamlessly integrating machine learning into operations.
Thomas has an impressive track record as a leader, having overseen two publicly funded open-source research programs in the field of AI, in collaboration with the German Aerospace Center. Today, he is at the forefront of AI-driven cybersecurity research at Smart Cyber Security GmbH and working on his low-budget bark beetle detection drone project – a testament to his enduring fascination with embedded systems.
Smart Cyber Security GmbH
Homepage – Git*hub|lab –Session
The world of open source computer vision has never been so exciting - and so challenging. With so many options available to you, what's the best way to solve your real world problem? The questions are always the same: Do I have enough data? Which model should I choose? How can I fine-tune and optimize the hyperparameters?
In collaboration with the German Aerospace Center, we investigated these questions to develop a model for quality assurance of CFRP tape laying, with only a small real data set fresh from production. We are very pleased to present a machine learning setup that can empirically answer these questions. Not only for us, but also for you - our setup can easily be transferred to your application!
Dive with us into the world of Open Source machine learning tools that are perfectly tailored for your next project. Discover the seamless integration of Hugging Face Model Hub, DvC and Ray Tune. You'll also gain unique insights into the fascinating world of CFRP tape laying, specifically how well different architectures of open source models perform on our small dataset.
If you want to level up your MLOps game and gain practical knowledge of the latest computer vision models and practices, this talk is a must for you. Don't miss the opportunity, and look forward to your next computer vision projects!