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Machine Learning 2.0 with Hugging Face

As amazing as state-of-the-art machine learning models are, training, optimizing, and deploying them remains a challenging endeavor that requires a significant amount of time, resources, and skills, all the more when different languages are involved. Unfortunately, this complexity prevents most organizations from using these models effectively, if at all.

In this session, we'll introduce you to Transformer models and what business problems you can solve with them. Then, we’ll show you how you can simplify and accelerate your machine learning projects end-to-end: experimenting, training, optimizing, and deploying. Along the way, we'll run some demos to keep things concrete and exciting!


Basic understanding of Machine Learning workflows, from experimentation to production

  • Basic understanding of Python


    • Understand why transfer learning and transformers are changing the ML game
    • Learn about the Hugging Face tools available to data scientists and developers
    • Learn how to quickly build and deploy ML applications based on state-of-the-art-models

  • Speaker


    Julien Simon
    Julien Simon is currently Chief Evangelist at Hugging Face. He's recently spent six years at Amazon Web Services where he was the Global Technical Evangelist for AI and Machine Learning. Prior to joining AWS, Julien served for ten years as CTO/VP Engineering in large-scale startups where he led large software and Ops teams in charge of thousands of servers worldwide.




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