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Study mode:
on
1
intro
2
preface
3
ml engineers' lives can be challenging
4
the current solution
5
who is noa
6
what is mlops
7
mlops is important to ml engineers
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the main components mlops should cover
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data challenges
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data versioning
11
data visualisations
12
experiments challenges
13
experiment tracking
14
the main components mlops should cover
15
models challenges
16
model registry
17
general ux tips
18
what is your favourite mlops experience? tell me!
Description:
Explore the world of MLOps in this conference talk from Conf42 Machine Learning 2023. Delve into the challenges faced by ML engineers and discover current solutions in the field. Learn about the importance of MLOps and its main components, including data versioning, data visualization, experiment tracking, and model registry. Gain insights into data challenges, experiment management, and model-related issues. Pick up valuable UX tips for MLOps implementations and engage with the speaker's invitation to share your favorite MLOps experiences.

A Hitchhiker's Guide to the MLOps Experience

Conf42
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