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The 7 Lines of Code You Need to Run Faster Real-time Inference

Posted Mar 10, 2023 | Views 682
# Enterprises
# ML Approach Adoption
# ML Solution Development and Operations
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Adrian Boguszewski
AI Software Evangelist @ Intel

AI Software Evangelist at Intel. Adrian graduated from the Gdansk University of Technology in the field of Computer Science 6 years ago. After that, he started his career in computer vision and deep learning. As a team leader of data scientists and Android developers for the previous two years, Adrian was responsible for an application to take a professional photo (for an ID card or passport) without leaving home. He is a co-author of the LandCover.ai dataset and he was teaching people how to do deep learning. His current role is to educate people about OpenVINO Toolkit. In his free time, he’s a traveler. You can also talk with him about finance, especially investments.

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SUMMARY

As an emerging sub-discipline, MLOps still needs to prove itself inside many enterprises where ML may present significant opportunities. Focused on the needs of the ML and Enterprise Architect this talk discusses some of the key areas which motivate the adoption of an MLOps approach to handling ML solution development and operations.

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