What we’re about
đź–– This virtual group is for data scientists, machine learning engineers, and open source enthusiasts.
Every month we’ll bring you diverse speakers working at the cutting edge of AI, machine learning, and computer vision.
- Are you interested in speaking at a future Meetup?
- Is your company interested in sponsoring a Meetup?
This Meetup is sponsored by Voxel51, the lead maintainers of the open source FiftyOne computer vision toolset. To learn more, visit the FiftyOne project page on GitHub.
Upcoming events (4+)
See all- April 26 - Berlin Computer Vision for Autonomous Driving WorkshopMotionLab.Berlin, Berlin
Date and Time
April 26, 2025 from 9:30 AM to 3:00 PM
Location
The Workshop will take place at MotionLab.Berlin, Bouchéstraße 12/Halle 20 in Berlin
Workshop Overview
This interactive workshop will guide participants through implementing computer vision techniques for autonomous driving applications. Attendees will gain practical experience working with Voxel51’s open source tools to analyze and understand the challenges in autonomous driving using the BDD100K dataset from Berkeley DeepDrive.
Bring your laptop and enthusiasm, food and drinks will be provided.
What You’ll Learn
- Fundamentals of computer vision for autonomous driving
- Exploring the BDD100K dataset and its diverse driving scenarios
- Implementing zero-shot classification for object recognition
- Working with YOLO variants for real-time object detection
- Extracting precise localization information with instance and panoptic segmentation algorithms
- Using image embeddings to extract meaningful insights from driving data
- Understanding key challenges in autonomous driving systems
Hands-On Activities
Participants will work through practical exercises using Python and Voxel51’s open-source tools to:
- Process and analyze driving imagery from diverse conditions
- Implement zero-shot classification for novel object detection
- Compare performance of different YOLO variants on autonomous driving data
- Build embeddings-based pipelines for scene understanding
- Explore approaches to handling edge cases in autonomous driving scenarios
Prerequisites
- Basic Python programming experience
- Familiarity with machine learning concepts
- Laptop with Python environment installed (setup instructions will be provided)
About the Instructors
Paula Ramos, PhD is a Senior Developer Relations Specialist at Voxel51. She specializes in helping developers implement effective computer vision solutions for autonomous systems and building a community around open-source computer vision tools.
Antonio Rueda-Toicen is an AI Engineer at Voxel51. He focuses on bridging the gap between cutting-edge computer vision research and practical autonomous driving implementations, creating accessible pathways for developers to leverage Voxel51’s technologies.
- Network event119 attendees from 36 groups hostingApril 29 - Model Optimization: Data Augmentation & Regularization WorkshopLink visible for attendees
When and Where
- April 29, 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 optimization strategies including data augmentation, dropout, batch normalization, and transfer learning. Implement an augmented network using a fruits dataset with models like VGG-16 and ResNet18, and analyze the 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.
- Network event38 attendees from 36 groups hostingMay 6 - Image Embeddings: Zero-shot Classification with CLIP WorkshopLink visible for attendees
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.
- Network event33 attendees from 36 groups hostingMay 13 - Object Detection & Instance Segmentation: YOLO in Practice WorkshopLink visible for attendees
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.
