DeepLearning.AI
Machine Learning Data Lifecycle in Production
DeepLearning.AI

Machine Learning Data Lifecycle 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

43,876 already enrolled

Course

Gain insight into a topic and learn the fundamentals

4.3

(808 reviews)

|

88%

Advanced level

Recommended experience

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

What you'll learn

  •  Identify responsible data collection for building a fair ML production system.

  • Implement feature engineering, transformation, and selection with TensorFlow Extended

  • Understand the data journey over a production system’s lifecycle and leverage ML metadata and enterprise schemas to address quickly evolving data.

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

13 quizzes

Course

Gain insight into a topic and learn the fundamentals

4.3

(808 reviews)

|

88%

Advanced level

Recommended experience

21 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 4 modules in this course

This week covers a quick introduction to machine learning production systems. More concretely you will learn about leveraging the TensorFlow Extended (TFX) library to collect, label and validate data to make it production ready.

What's included

12 videos5 readings4 quizzes1 programming assignment1 ungraded lab

Implement feature engineering, transformation, and selection with TensorFlow Extended by encoding structured and unstructured data types and addressing class imbalances

What's included

12 videos2 readings3 quizzes1 programming assignment3 ungraded labs

Understand the data journey over a production system’s lifecycle and leverage ML metadata and enterprise schemas to address quickly evolving data.

What's included

8 videos3 readings3 quizzes1 programming assignment2 ungraded labs

Combine labeled and unlabeled data to improve ML model accuracy and augment data to diversify your training set.

What's included

6 videos4 readings3 quizzes3 ungraded labs

Instructor

Instructor ratings
4.1 (234 ratings)
Robert Crowe
DeepLearning.AI
3 Courses55,873 learners

Offered by

DeepLearning.AI

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4.3

808 reviews

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