North Rhine-Westphalia AI, ML and Computer Vision Meetup

Register for the Zoom

When and Where

• May 6, 2025
• 6:30 PM to 8:30 PM CET | 9:30 AM to 11:30 AM Pacific
• Workshops are delivered over Zoom

About the Workshop

Join us for a 12-part, hands-on series that teaches you how to work with images, build and train models, and explore tasks like image classification, segmentation, object detection, and image generation. Each session combines straightforward explanations with practical coding in PyTorch and FiftyOne, allowing you to learn core skills in computer vision and apply them to real-world tasks.

In this session, we’ll cover image embeddings, vision transformers, and CLIP. Build a model for zero-shot classification and semantic search using CLIP, then inspect how image embeddings influence predictions with FiftyOne.

These are hands-on maker workshops that make use of GitHub Codespaces, Kaggle notebooks, and Google Colab environments, so no local installation is required (though you are welcome to work locally if preferred!)

Workshop Resources

You can find the workshop materials in this GitHub repository.

About the Instructor

Antonio Rueda-Toicen, an AI Engineer in Berlin, has extensive experience in deploying machine learning models and has taught over 300 professionals. He is currently a Research Scientist at the Hasso Plattner Institute. Since 2019, he has organized the Berlin Computer Vision Group and taught at Berlin’s Data Science Retreat. He specializes in computer vision, cloud technologies, and machine learning. Antonio is also a certified instructor of deep learning and diffusion models in NVIDIA’s Deep Learning Institute.

Register for the Zoom

When and Where

• May 13, 2025
• 6:30 PM to 8:30 PM CET | 9:30 AM to 11:30 AM Pacific
• Workshops are delivered over Zoom

About the Workshop

Join us for a 12-part, hands-on series that teaches you how to work with images, build and train models, and explore tasks like image classification, segmentation, object detection, and image generation. Each session combines straightforward explanations with practical coding in PyTorch and FiftyOne, allowing you to learn core skills in computer vision and apply them to real-world tasks.

In this session, we’ll introduce object detection and instance segmentation methods. Build a YOLO-based network to perform object detection and instance segmentation, and analyze detection results with FiftyOne.

These are hands-on maker workshops that make use of GitHub Codespaces, Kaggle notebooks, and Google Colab environments, so no local installation is required (though you are welcome to work locally if preferred!)

Workshop Resources

You can find the workshop materials in this GitHub repository.

About the Instructor

Antonio Rueda-Toicen, an AI Engineer in Berlin, has extensive experience in deploying machine learning models and has taught over 300 professionals. He is currently a Research Scientist at the Hasso Plattner Institute. Since 2019, he has organized the Berlin Computer Vision Group and taught at Berlin’s Data Science Retreat. He specializes in computer vision, cloud technologies, and machine learning. Antonio is also a certified instructor of deep learning and diffusion models in NVIDIA’s Deep Learning Institute.

Register for the Zoom

About the Workshop

Want greater visibility into the quality of your computer vision datasets and models? Then join us for this free 90-minute, hands-on workshop to learn how to leverage the open source FiftyOne computer vision toolset.

At the end of the workshop you’ll be able to:

• Visualize complex datasets
• Explore embeddings
• Analyze and improve models
• Perform advanced data curation
• Integrations

This workshop will explore the importance of taking a data-centric approach to computer vision workflows. We will start with importing and exploring visual data, then move to querying and filtering. Next, we’ll look at ways to extend FiftyOne’s functionality and simplify tasks using plugins and native integrations. We’ll generate candidate ground truth labels, and then wrap things up by evaluating the results of fine tuning a foundational model.

Prerequisites: working knowledge of Python and basic computer vision concepts.

All attendees will get access to the tutorials, videos, and code examples used in the workshop

Register for the Zoom

When and Where

• May 20, 2025
• 6:30 PM to 8:30 PM CET | 9:30 AM to 11:30 AM Pacific
• Workshops are delivered over Zoom

About the Workshop

Join us for a 12-part, hands-on series that teaches you how to work with images, build and train models, and explore tasks like image classification, segmentation, object detection, and image generation. Each session combines straightforward explanations with practical coding in PyTorch and FiftyOne, allowing you to learn core skills in computer vision and apply them to real-world tasks.

In this session, we’ll explore image generation techniques using diffusion models. Participants will build a U-Net-based model to generate MNIST-like images and then inspect the generated outputs with FiftyOne.

These are hands-on maker workshops that make use of GitHub Codespaces, Kaggle notebooks, and Google Colab environments, so no local installation is required (though you are welcome to work locally if preferred!)

Workshop Resources

You can find the workshop materials in this GitHub repository.

About the Instructor

Antonio Rueda-Toicen, an AI Engineer in Berlin, has extensive experience in deploying machine learning models and has taught over 300 professionals. He is currently a Research Scientist at the Hasso Plattner Institute. Since 2019, he has organized the Berlin Computer Vision Group and taught at Berlin’s Data Science Retreat. He specializes in computer vision, cloud technologies, and machine learning. Antonio is also a certified instructor of deep learning and diffusion models in NVIDIA’s Deep Learning Institute.