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September 12 & 13, 2023
Virtual

ML-at-Scale: ‘23

The leading event for applying machine learning at scale, from open source to high-performance computing.
September 12 & 13, 2023
Virtual

Welcome to ML-at-Scale ‘23

This event brings together experts in machine learning to discuss the challenges and opportunities of achieving ML-at-Scale.

Today’s ML developers train models that have an infinite number of parameters on limited compute resources. ML teams are typically small in size, limiting the scope of achievable projects. Combine those challenges with the endless state-of-the-art models and training sets and seemingly limitless number of deployment options, ML practitioners have their hands full. Achieving “ML-at-Scale” means identifying the hardest problems but also discovering the biggest opportunities for applying ML today. 

At ML-at-Scale ‘23’, you will have the opportunity to participate in hands-on workshops, attend keynote speeches from leading machine learning experts, and network with open source leaders and enterprise technology gurus that address the complexities of performing machine learning at-scale.

ML-at-Scale ‘23 is an opportunity for machine learning and deep learning practitioners to explore the latest advancements in scaling machine learning, from open source to high-performance computing. If machine learning is pivotal to your business, this conference is designed to help you put the latest ideas and tools into practice and take your AI/ML initiatives to the next level. 

Register now for ML-at-Scale ‘23’ and join us for two days of groundbreaking insight and inspiration.

Why Attend ML-at-Scale?

Learn

Hear from the very best in machine learning on cutting-edge techniques and best practices. From industry experts to open source leaders, we’ll be premiering sessions on topics like performing model training, transforming your data pipelines, practicing fairness and ethics in AI, and more.

Practice

Engage in hands-on workshops alongside the best in data science to broaden your AI toolkit. You should leave ML-at-Scale with new techniques and skills as well as familiarity with open source software from across the machine learning landscape. 

Engage

Bring your own tips of the trade and pick up knowledge from others across ML! Networking is key to any event, so we’ll coordinate breakout rooms and dedicated communication channels for attendees to meet new collaborators and deepen their connections with ML peers.

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