Amazon SageMaker is a fully managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. Julien Simon offers a quick overview of SageMaker. Then, using Jupyter notebooks, he dives into the more advanced features of this service: state-of-the-art built-in algorithms streaming training data with pipe mode, predicting in batch mode, performing hyperparameter optimization, and of course, running deep learning libraries.
This session is sponsored by Amazon Web Services.
Julien Simon is an artificial intelligence and machine learning evangelist for EMEA at Amazon Web Services, where he focuses on helping developers and enterprises bring their ideas to life. Previously, Julien served for 10 years as CTO and vice president of engineering at top-tier web startups, where he led large software and ops teams in charge of thousands of servers worldwide. In the process, he fought his way through a wide range of technical, business, and procurement issues, which helped him gain a deep understanding of physical infrastructure, its limitations, and how cloud computing can help. He frequently speaks at conferences and actively blogs. Julien also holds all eight AWS certifications.
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