DeepLearning.AI
Machine Learning Modeling Pipelines in Production
DeepLearning.AI

Machine Learning Modeling Pipelines in Production

This course is part of Machine Learning Engineering for Production (MLOps) Specialization

Taught in English

Some content may not be translated

Robert Crowe

Instructor: Robert Crowe

31,760 already enrolled

Course

Gain insight into a topic and learn the fundamentals

4.4

(410 reviews)

|

87%

Advanced level

Recommended experience

23 hours (approximately)
Flexible schedule
Learn at your own pace

What you'll learn

  • Apply techniques to manage modeling resources and best serve batch and real-time inference requests.

  • Use analytics to address model fairness, explainability issues, and mitigate bottlenecks.

Details to know

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Assessments

12 quizzes

Course

Gain insight into a topic and learn the fundamentals

4.4

(410 reviews)

|

87%

Advanced level

Recommended experience

23 hours (approximately)
Flexible schedule
Learn at your own pace

See how employees at top companies are mastering in-demand skills

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Build your subject-matter expertise

This course is part of the Machine Learning Engineering for Production (MLOps) Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate
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There are 5 modules in this course

Learn how to effectively search for the best model that will scale for various serving needs while constraining model complexity and hardware requirements.

What's included

10 videos5 readings2 quizzes2 app items1 ungraded lab

Learn how to optimize and manage the compute, storage, and I/O resources your model needs in production environments during its entire lifecycle.

What's included

13 videos7 readings2 quizzes

Implement distributed processing and parallelism techniques to make the most of your computational resources for training your models efficiently.

What's included

6 videos5 readings2 quizzes1 app item

Use model performance analysis to debug and remediate your model and measure robustness, fairness, and stability.

What's included

12 videos6 readings3 quizzes3 ungraded labs

Learn about model interpretability - the key to explaining your model’s inner workings to laypeople and expert audiences and how it promotes fairness and helps address regulatory and legal requirements for different use cases.

What's included

11 videos12 readings3 quizzes1 app item

Instructor

Instructor ratings
4.4 (106 ratings)
Robert Crowe
DeepLearning.AI
3 Courses56,643 learners

Offered by

DeepLearning.AI

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4.4

410 reviews

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