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MLOps Without Much Ops - Building Efficient Machine Learning Systems

Offered By: Toronto Machine Learning Series (TMLS) via YouTube

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MLOps Courses Data Science Courses Machine Learning Courses DevOps Courses Cloud Computing Courses Scalability Courses Data Pipelines Courses

Course Description

Overview

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Explore a comprehensive approach to building efficient machine learning systems with minimal operational overhead in this insightful conference talk. Learn about the growing ecosystem of tools and best practices that enable even small teams to be highly productive at a reasonable scale. Discover the advantages of a Platform as a Service (PaaS) approach and gain practical insights into implementing modern, no-nonsense data pipelines. Examine real-world examples with open-source code to understand how the entire toolchain functions under realistic constraints. Gain valuable advice on the future of machine learning for "reasonable" companies, drawing from the speaker's experience in both small and large organizations. Delve into the intersection of language, reasoning, and learning as presented by Jacopo Tagliabue, Lead AI Scientist at Coveo, who brings a wealth of experience from his roles as a former CTO, researcher, and innovator in the field of artificial intelligence.

Syllabus

MLOps Without Much Ops


Taught by

Toronto Machine Learning Series (TMLS)

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