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 event35 attendees from 12 groups hostingMay 8 - Developing FiftyOne Plugins WorkshopLink visible for attendees
When
May 8, 2024 at 9 AM Pacific for 90 minutesWhere
Virtually over Zoom: https://voxel51.com/computer-vision-events/fiftyone-plugins-workshop-authoring-data-centric-ai-applications-may-8-2024-2/About the Workshop
Are you ready to take your computer vision tooling to the next level? Open source FiftyOne is the most flexible computer vision toolkit on the planet. By tapping into its builtin Plugin framework, you can extend your FiftyOne experience and streamline your workflows, building Gradio-like applications with data at their core.From concept interpolation to image deduplication, optical character recognition, and even curating your own AI art gallery by adding generated images directly into a dataset, your imagination is the only limit. Join us to discover how you can unleash your creativity and interact with data like never before.
In the first part of the workshop weâll cover:
- FiftyOne Plugins â what are they?
- Installing a plugin
- Creating your own Python plugin
- Python plugin tips
- Creating your own JavaScript plugin
- Publishing your plugin
Prerequisites
A working knowledge of Python and basic familiarity with FiftyOne. All attendees will get access to the tutorials, videos, and code examples used in the workshop.Resources
Check out some these popular plugins:
- VoxelGPT: AI Assistant for Computer Vision
- Image Quality Issues
- Image Deduplication
- AI Art Gallery
- Optical Character Recognition
- Visual Question Answering
Resources for the workshop:
- FiftyOne Plugins Documentation
- Python Operators API Docs
- FiftyOne Plugins Repo
- Plugins Channel in FiftyOne Community Slack
Videos:
- Network event49 attendees from 14 groups hostingMay 8 - AI, Machine Learning and Computer Vision MeetupLink visible for attendees
When
May 8, 2024 â 10:00 AM Pacific / 1:00 PM EasternWhere
Virtual / Zoom: https://voxel51.com/computer-vision-events/may-8-2024-ai-machine-learning-data-science-meetup/To Infer or To Defer: Hazy Oracles in Human+AI Collaboration
This talk explores the evolving dynamics of human+AI collaboration, focusing on the concept of the human as a âhazy oracleâ rather than an infallible source. It outlines the journey of integrating AI systems more deeply into practical applications through human+AI cooperation, discussing the potential value and challenges. The discussion includes the modeling of interaction errors and the strategic choices between immediate AI inference or seeking additional human input, supported by results from a user study on optimizing these collaborations.
About the Speaker
Jason Corso is a Professor of Robotics, Electrical Engineering, and Computer Science at the University of Michigan, and Co-Founder / Chief Scientist at AI startup Voxel51. His research spans computer vision, robotics, and AI, with over 150 peer-reviewed publications.
From Research to Industry: Bridging Real-World Applications with Anomalib at the CVPR VAND Challenge
This talk highlights the role of Anomalib, an open-source deep learning framework, in advancing anomaly detection within AI systems, particularly showcased at the upcoming CVPR Visual Anomaly and Novelty Detection (VAND) workshop. Anomalib integrates advanced algorithms and tools to facilitate both academic research and practical applications in sectors like manufacturing, healthcare, and security. It features capabilities such as experiment tracking, model optimization, and scalable deployment solutions. Additionally, the discussion will include Anomalibâs participation in the VAND challenge, focusing on robust real-world applications and few-shot learning for anomaly detection.
About the Speaker
Samet Akcay, an AI research engineer and a tech lead, specializes in semi/self-supervised, zero/few-shot anomaly detection, and multi-modality. He is recently known for his open-source contributions to the ML/DL community. He is the lead author of anomalib, a major open-source anomaly detection library. He also maintains the OpenVINO Training Extensions, a low-code transfer learning framework for building computer vision models.
Learning Robot Perception and Control using Vision with Action
To achieve general utility, robots must continue to learn in unstructured environments. In this talk, I describe how our mobile manipulation robot uses vision with action to 1) learn visual control, 2) annotate its own training data, and 3) learn to estimate depth for new objects and the environment. Using these techniques, I describe how I led a small group to win consecutive robot competitions against teams from Stanford, MIT, and other Universities.
About the Speaker
Brent Griffin is the Perception Lead at Agility Robotics and was previously an assistant research scientist at the University of Michigan conducting research at the intersection of computer vision, control, and robot learning. He is lead author on publications in all of the top IEEE conferences for computer vision, robotics, and control, and his work has been featured in Popular Science, in IEEE Spectrum, and on the Big Ten Network.
Anomaly Detection with Anomalib and FiftyOne
Most anomaly detection techniques are unsupervised, meaning that anomaly detection models are trained on unlabeled non-anomalous data. Developing the highest-quality dataset and data pipeline is essential to training robust anomaly detection models.
In this brief walkthrough, I will illustrate how to leverage open-source FiftyOne and Anomalib to build deployment-ready anomaly detection models. First, we will load and visualize the MVTec AD dataset in the FiftyOne App. Next, we will use Albumentations to test out augmentation techniques. We will then train an anomaly detection model with Anomalib and evaluate the model with FiftyOne.
About the Speaker
Jacob Marks is a Senior Machine Learning Engineer and Researcher at Voxel51, where he leads open source efforts in vector search, semantic search, and generative AI for the FiftyOne data-centric AI toolkit.
Prior to joining Voxel51, Jacob worked at Google X, Samsung Research, and Wolfram Research. - Network event4 attendees from 12 groups hostingMay 29 - Getting Started with FiftyOne WorkshopLink visible for attendees
When
May 29, 2024 at 9 AM Pacific for 90 minutesWhere
Virtually over Zoom: https://voxel51.com/computer-vision-events/getting-started-with-fiftyone-workshop-may-29-2024/About the Workshop
Want greater visibility into the quality of your computer vision datasets and models? Then join Allen Lee, Machine Learning Engineer at Voxel51, for this free 90 minute, hands-on workshop to learn how to leverage the open source FiftyOne computer vision toolset.In the first part of the workshop weâll cover:
- FiftyOne Basics (terms, architecture, installation, and general usage)
- An overview of useful workflows to explore, understand, and curate your data
- How FiftyOne represents and semantically slices unstructured computer vision data
The second half will be a hands-on introduction to FiftyOne, where you will learn how to:
- Load datasets from the FiftyOne Dataset Zoo
- Navigate the FiftyOne App
- Programmatically inspect attributes of a dataset
- Add new sample and custom attributes to a dataset
- Generate and evaluate model predictions
- Save insightful views into the data
Prerequisites are a working knowledge of Python and basic computer vision. All attendees will get access to the tutorials, videos, and code examples used in the workshop.
- Network event11 attendees from 3 groups hostingMay 30, 2024 AI, Machine Learning and Data Science MeetupGitHub, San Francisco, CA
Pre-registering for the event is mandatory. Sign up here:
https://voxel51.com/computer-vision-events/may-30-2024-ai-machine-learning-data-science-meetup/
Date and Time
May 30, 5:30 PM to 8:00 PM Pacific
Location
The Meetup will take place at GitHubâs offices in San Francisco. Note that pre-registration is mandatory.
88 Colin P Kelly Jr St, San Francisco, CA 94107
Lessons Learned fine-tuning Llama2 for Autonomous Agents
In this talk, Rahul Parundekar, Founder of A.I. Hero, Inc. does a deep dive into the practicalities and nuances of making LLMs more effective and efficient. Heâll share hard-earned lessons from the trenches of LLMOps on Kubernetes, covering everything from the critical importance of data quality to the choice of fine-tuning techniques like LoRA and QLoRA. Rahul will share insights into the quirks of fine-tuning LLMs like Llama2, the need for looking beyond loss metrics and benchmarks for model performance, and the pivotal role of iterative improvement through user feedback â all learned through his work on fine-tuning an LLM for retrieval-augmented generation and autonomous agents. Whether youâre a seasoned AI professional or just starting, this talk will equip you with the knowledge of when and why you should fine-tune, to the long-term strategies to push the boundaries of whatâs possible with LLMs, to building a performant framework on top of Kubernetes for fine-tuning at scale.
Speaker: Rahul Parundekar is the founder of A.I. Hero, Inc., a seasoned engineer, and architect with over 15 years of experience in AI development, focusing on Machine Learning and Large Language Model Operations (MLOps and LLMOps). AI Hero automates mundane enterprise tasks through agents, utilizing a framework for fine-tuning LLMs with both open and closed-source models to enhance agent autonomy.
Multi-Modal Visual Question Answering (VQA) using UForm tiny models with Milvus vector database
UForm is a multimodal AI library that will help you understand and search visual and textual content across various languages. UForm not only supports RAG chat use-cases, but is also capable of Visual Question Answering (VQA). Compact custom pre-trained transformer models can run anywhere from your server farm down to your laptop. Iâll be giving a demo of RAG and VQA using Milvus vector database.
Speaker: Christy Bergman is a passionate Developer Advocate at Zilliz. She previously worked in distributed computing at Anyscale and as a Specialist AI/ML Solutions Architect at AWS.
Speaker: Ash Vardanian is the Founder of Unum Cloud. With a background in Astrophysics, his work today primarily lies in the intersection of Theoretical Computer Science, High-Performance Computing, and AI Systems Design.
Combining Hugging Face Transformer Models and Image Data with FiftyOne
Datasets and Models are the two pillars of modern machine learning, but connecting the two can be cumbersome and time-consuming. In this lightning talk, you will learn how the seamless integration between Hugging Face and FiftyOne simplifies this complexity, enabling more effective data-model co-development. By the end of the talk, you will be able to download and visualize datasets from the Hugging Face hub with FiftyOne, apply state-of-the-art transformer models directly to your data, and effortlessly share your datasets with others.
Speaker: Jacob Marks, PhD is a Machine Learning Engineer and Developer Evangelist at Voxel51, where he leads open source efforts in vector search, semantic search, and generative AI for the FiftyOne data-centric AI toolkit.
Prior to joining Voxel51, Jacob worked at Google X, Samsung Research, and Wolfram Research.Strategies for Enhancing the Adoption of Open Source Libraries: A Case Study on Albumentations.ai
In this presentation, we explore key strategies for boosting the adoption of open-source libraries, using Albumentations.ai as a case study. We will cover the importance of community engagement, continuous innovation, and comprehensive documentation in driving a projectâs success. Through the lens of Albumentations.aiâs growth, attendees will gain insights into effective practices for promoting their open source projects within the machine learning and broader developer communities.
Speaker: Vladimir Iglovikov, PhD is a co-creator of Albumentations.ai, a Kaggle Grandmaster.
Past events (88)
See all- Network event50 attendees from 12 groups hostingApril 24 - Getting Started with FiftyOne WorkshopThis event has passed