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Learner Reviews & Feedback for Machine Learning in Production by DeepLearning.AI

4.8
stars
3,342 ratings

About the Course

In this Machine Learning in Production course, you will build intuition about designing a production ML system end-to-end: project scoping, data needs, modeling strategies, and deployment patterns and technologies. You will learn strategies for addressing common challenges in production like establishing a model baseline, addressing concept drift, and performing error analysis. You’ll follow a framework for developing, deploying, and continuously improving a productionized ML application. Understanding machine learning and deep learning concepts is essential, but if you’re looking to build an effective AI career, you need experience preparing your projects for deployment as well. Machine learning engineering for production combines the foundational concepts of machine learning with the skills and best practices of modern software development necessary to successfully deploy and maintain ML systems in real-world environments. Week 1: Overview of the ML Lifecycle and Deployment Week 2: Modeling Challenges and Strategies Week 3: Data Definition and Baseline...

Top reviews

PK

Jan 8, 2023

Excellent course! Andrew Ng is an exceptional human being. His teaching skill are impeccable and you as a student actually are interested in what he's telling you and learn more.

DC

May 20, 2021

Practical and well-structured advices throughout the lifecycle of ML. Examples from real world problems & experiences make the advices more tangible and helps to reflect on own problems.

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576 - 579 of 579 Reviews for Machine Learning in Production

By Shahzad H

•

Jul 11, 2023

We need more practical graded exercise lab to hone our technical skills, the labs in most cases are easy and not job specific

By Nikita M

•

Jul 6, 2025

Useless and boring

By S. H

•

Aug 19, 2024

Coursera refuses to issue the specialisation certificate even though I spent over 300 euros and completed all courses. If I was told this beforehand, I would not spend anything on the course. The customer support team has not been helpful.

By Youssef A

•

Dec 10, 2022

too much theory, the course could include some lab practices and be more fun and memorable