Machine Learning in Production

Taught in English

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Gain insight into a topic and learn the fundamentals

Andrew Ng

Instructor: Andrew Ng

Top Instructor


(2,917 reviews)

Intermediate level

Recommended experience

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

What you'll learn

  • Identify key components of the ML project lifecycle, pipeline & select the best deployment & monitoring patterns for different production scenarios.

  • Optimize model performance and metrics by prioritizing  disproportionately important examples that represent key slices of a dataset.

  • Solve production challenges regarding structured, unstructured, small, and big data, how label consistency is essential, and how you can improve it.

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There are 3 modules in this course

This week covers a quick introduction to machine learning production systems focusing on their requirements and challenges. Next, the week focuses on deploying production systems and what is needed to do so robustly while facing constantly changing data.

What's included

8 videos3 readings2 quizzes1 app item2 ungraded labs

This week is about model strategies and key challenges in model development. It covers error analysis and strategies to work with different data types. It also addresses how to cope with class imbalance and highly skewed data sets.

What's included

16 videos2 readings2 quizzes1 ungraded lab

This week is all about working with different data types and ensuring label consistency for classification problems. This leads to establishing a performance baseline for your model and discussing strategies to improve it given your time and resources constraints.

What's included

17 videos5 readings2 quizzes2 ungraded labs


Instructor ratings
4.9 (955 ratings)
Andrew Ng

Top Instructor

44 Courses7,444,062 learners

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