What weâre about
đ This virtual group is for data scientists, machine learning engineers, and open source enthusiasts.
Every month weâll bring you two diverse speakers working at the cutting edge of data science, machine learning, AI and computer vision.
- Are you interested in speaking at a future Meetup?
- Is your company interested in sponsoring a Meetup?
Contact the Meetup organizers!
This Meetup is sponsored by Voxel51, the lead maintainers of the open source FiftyOne computer vision toolset. To learn more about FiftyOne, visit the project page on GitHub.
đŁ Past Speakers
* Sage Elliott at Union.ai
* Michael Wornow at Microsoft
* Argo Saakyan at Veryfi
* Justin Trugman at Softwaretesting.ai
* Johannes Flotzinger at UniversitĂ€t der Bundeswehr MĂŒnchen
* Harpreet Sahota at Deci,ai
* Nora Gourmelon at Friedrich-Alexander-UniversitĂ€t Erlangen-NĂŒrnberg
* Reid Pryzant at Microsoft
* David Mezzetti at NeuML
* Chaitanya Mitash at Amazon Robotics
* Fan Wang at Amazon Robotics
* Mani Nambi at Amazon Robotics
* Joy Timmermans at Secury360
* Eduardo Alvarez at Intel
* Minye Wu at KU Leuven
* Jizhizi Li at University of Sydney
* Raz Petel at SightX
* Karttikeya Mangalam at UC Berkeley
* Dolev Ofri-Amar at Weizmann Institute of Science
* Roushanak Rahmat, PhD
* Folefac Martins
* Zhixi Cai at Monash University
* Filip Haltmayer at Zilliz
* Stephanie Fu at MIT
* Shobhita Sundaram at MIT
* Netanel Tamir at Weizmann Institute of Science
* Glenn Jocher at Ultralytics
* Michal Geyer at Weizmann Institute of Science
* Narek Tumanya at Weizmann Institute of Science
* Jerome Pasquero at Sama
* Eric Zimmermann at Sama
* Victor Anton at Wildlife.ai
* Shashwat Srivastava at Opendoor
* Eugene Khvedchenia at Deci.ai
* Hila Chefer at Tel-Aviv University
* Zhuo Wu at Intel
* Chuan Guo at University of Alberta
* Dhruv Batra Meta & Georgia Tech
* Benjamin Lahner at MIT
* Jiajing Chen at Syracuse University
* Soumik Rakshit at Weights & Biases
* Jiajing Chen at Syracuse University
* Paula Ramos, PhD at Intel
* Vishal Rajput at Skybase
* Cameron Wolfe at Alegion/Rice University
* Julien Simon at Hugging Face
* Kris Kitani at Carnegie Mellon University
* Anna Kogan at OpenCV.ai
* Kacper Ćukawski at Qdrant
* Sri Anumakonda
* Tarik Hammadou at NVIDIA
* Zain Hasan at Weaviate
* Jai Chopra at LanceDB
* Sven Dickinson at University of Toronto & Samsung
* Nalini Singh at MIT
đ Resources
* YouTube Playlist of previous Meetups
* Recap blogs including Q&A and speaker resource links
Upcoming events (4+)
See all- 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, weâll 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 Berlinâs 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 NVIDIAâs 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, weâll 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 Berlinâs 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 NVIDIAâs 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, weâll 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 Berlinâs 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 NVIDIAâs Deep Learning Institute.
- Network event21 attendees from 36 groups hostingMay 20 - Image Generation: Diffusion Models & U-Net WorkshopLink visible for attendees
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, weâll 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 Berlinâs 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 NVIDIAâs Deep Learning Institute.
Past events (150)
See all- Network event427 attendees from 36 groups hostingApril 24, 2025 - AI, Machine Learning and Computer Vision MeetupThis event has passed
