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

4.8
stars
3,085 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

RG

Jun 4, 2021

really a great course. It'll really change your way of thinking ML in production use and will help you better understand how can you leverage the power of ML in a way that I'll really create a value

DT

Aug 14, 2021

Excellent course, as always. Very well explain for both Data Sicientist, Software engineer and Manager (with some basics undertsanding of ML). One of these courses that Data Sientist should follow.

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526 - 542 of 542 Reviews for Machine Learning in Production

By Diego L

Jun 9, 2021

It is really a nice conversation with Andrew Ng over some problems that you face when you try to put model on production, define projects and manage it. But, the frameworks that he proposes are totally general and this course has technical debts.

By jitao f

Aug 6, 2022

I have worked in AI powered healthcare imaging industry for some years. Most of concept mentioned are our daily routaine. It is good to catch them up with constructed courses but I was expecting more juciy.

By Kenan M

Mar 11, 2022

Consice and Vocational , especial to those working on unstructured data. I enjoyed it. Thanks

By Prabhanjan J

May 16, 2023

Weeks 2 and 3 were too much into theory. There wasn't much practice and application.

By Yaolin W

Oct 22, 2023

1) too shallow. 2) too many repeating content. Overall I don't feel very helpful

By diego p

Jul 20, 2021

Much more a high level course respect to what i expected

By Kiran R

Sep 25, 2021

very boring and should not be part of specialization

By محمد ا

May 19, 2023

the course was full of videos without practice

By Leandro K d O

Jun 13, 2021

I wish we had more practical exercises

By SRIKANTH M

Sep 7, 2021

its very good experience

By Gal H

May 7, 2024

tensorflow..

By Tman

Apr 4, 2023

Well, I am a big fan of Andrew Ng, his initial ML course is what kickstarted my career change from a computer scientist to an established data scientist, I quite liked the Deep Learning Specalization, but this course is absolutely not what I hoped it would be. Explaining what a confusion matrix is in an MLOps course? Explaining precision, recall and F1 score? Come on. That is not content I want to hear about when paying for an MLOps course. Data augmentation and feature engineering? Also, not MLOps topics. A lot of important topics are briefly discussed, but not in detail. Quite a bit of content is rehashed from the Deep Learning Specalization. Good content, but this course is not the right place for that.

By Matthieu G

Feb 28, 2024

I was quite disappointed, as it feel that this 1 week course could have been summarised in a 15min article: there are a lot of generalities, repetitions... and no hands-on assignments where you are effectively expected to code something (which is, to my point, fundamental to get something of ML mooc).

By Prudvi R

Jul 18, 2024

This course overlaps a lot with Structuring ML project course of Deep learning specialization. I found most of the concepts repetitive. I found no value in this course.

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 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