Duke University
MLOps Tools: MLflow and Hugging Face
Duke University

MLOps Tools: MLflow and Hugging Face

Noah Gift
Alfredo Deza

Instructors: Noah Gift

8,043 already enrolled

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Gain insight into a topic and learn the fundamentals.
3.8

(37 reviews)

Advanced level

Recommended experience

25 hours to complete
3 weeks at 8 hours a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
3.8

(37 reviews)

Advanced level

Recommended experience

25 hours to complete
3 weeks at 8 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Create new MLflow projects to create and register models.

  • Use Hugging Face models and datasets to build your own APIs.

  • Package and deploy Hugging Face to the Cloud using automation.

Details to know

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Assessments

10 assignments

Taught in English

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This course is part of the MLOps | Machine Learning Operations Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 4 modules in this course

In this module, you will learn what MLflow is and how to use it. You’ll install MLflow and perform basic operations like registering runs, models, and artifacts. Then, you’ll create an MLflow project for reproducible results. Finally, you’ll understand how to use a registry with MLflow models and reference artifacts from the API.

What's included

13 videos12 readings3 assignments2 discussion prompts1 ungraded lab

In this module, you will learn the basics of the Hugging Face platform. You will use some of its features like its repositories so that you can store models and datasets. Finally, you will learn how to add and use models and datasets using Hugging Face APIs as well as the web interface.

What's included

14 videos9 readings1 assignment1 ungraded lab

In this module, you will learn how to containerize Hugging Face models and use the FastAPI framework to serve the model with an interactive HTTP API endpoint. Once you understand how to put everything together, you’ll use automation for speed and reproducibility. Finally, you’ll use Azure and Docker Hub to store the containers so that they can be used later for deployments.

What's included

13 videos9 readings3 assignments1 ungraded lab

In this module, you will learn how to fine-tune Hugging Face models by using pre-existing models and then modifying (fine-tuning) them with additional data. You’ll also use Azure to deploy the container and learn how to troubleshoot it. Finally, you’ll also see how to deploy a model to Hugging Face spaces.

What's included

17 videos10 readings3 assignments5 ungraded labs

Instructors

Instructor ratings
4.5 (9 ratings)
Noah Gift
Duke University
40 Courses145,760 learners

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Duke University

Recommended if you're interested in Machine Learning

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3.8

37 reviews

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    8.10%

ND
5

Reviewed on Aug 21, 2024

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