YoVDO

An Overview of Common ML Serving Architectures

Offered By: MLOps.community via YouTube

Tags

Machine Learning Courses Signal Processing Courses MLOps Courses Bayesian Statistics Courses Data Engineering Courses

Course Description

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Explore common machine learning serving architectures in this 18-minute conference talk by Rebecca Taylor, tech lead of Personalization at Lidl e-commerce. Gain insights into the disconnect between academic teachings and industry practices in model deployment. Learn about the constraints that impact deployment design, including unique data setups, platform configurations, and financial limitations. Discover how to build flexible designs that accommodate these constraints. Benefit from Rebecca's extensive experience in MLOps, electronic engineering, and data science consulting, as well as her academic background in Bayesian Statistics and engineering.

Syllabus

An Overview of Common ML Serving Architectures // Rebecca Taylor // DE4AI


Taught by

MLOps.community

Related Courses

Introduction to Probability, Statistics, and Random Processes
University of Massachusetts Amherst via Independent
Bayesian Statistics
Duke University via Coursera
Bayesian Statistics: From Concept to Data Analysis
University of California, Santa Cruz via Coursera
Improving your statistical inferences
Eindhoven University of Technology via Coursera
Bayesian Statistics: Techniques and Models
University of California, Santa Cruz via Coursera