Chevron Left
Back to Machine Learning Modeling Pipelines in Production

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

315 ratings

About the Course

In the third course of Machine Learning Engineering for Production Specialization, you will build models for different serving environments; implement tools and techniques to effectively manage your modeling resources and best serve offline and online inference requests; and use analytics tools and performance metrics to address model fairness, explainability issues, and mitigate bottlenecks. Understanding machine learning and deep learning concepts is essential, but if you’re looking to build an effective AI career, you need production engineering capabilities as well. Machine learning engineering for production combines the foundational concepts of machine learning with the functional expertise of modern software development and engineering roles to help you develop production-ready skills. Week 1: Neural Architecture Search Week 2: Model Resource Management Techniques Week 3: High-Performance Modeling Week 4: Model Analysis Week 5: Interpretability...

Top reviews


Sep 13, 2021

Excellent content and lectures from Mr. Robert . Thank you very much Sir for the excellent way of explaining these difficult topics . Thank you !!!


Oct 20, 2021

I enjoyed this course a lot. It gave me a lot of ideas on how I can improve my models and make my workflow more efficient. Thank you.

Filter by:

26 - 50 of 60 Reviews for Machine Learning Modeling Pipelines in Production

By Ankit P

Apr 26, 2022

It was really a wonderful and amazing course. I really learnt about what all goes in creating a successful ML project

By vadim m

Aug 4, 2021

Covers a lot of hot topics related to ML Modeling pipelines in production with great breadth and depth.

By Reza M

Sep 14, 2021

This is very helpful course to understand the life of model specially after its deployment.

By Cees R

Oct 15, 2021

This course filled in some black holes in my knowledge and I found it very helpful.

By amadou d

Aug 8, 2021

Excellent!! Ver, Very Very Good. Learn a lot. Thank you for sharing.

By Sri V D

Jan 6, 2023

Excellent introduction to pipelines for production ML.

By Daniel W

Jun 9, 2022

Great course, probably the best in the specialisation.

By fernandes m

Sep 24, 2021

The first course of MLOps, and the best.

By Thiago P

Feb 1, 2022

Really liked the last week content


May 14, 2022

This is a very detail course

By Илья В

Sep 9, 2021

great course, a lot of stuff

By Liang L

Jul 22, 2021

Good content and hands on.

By Pedro C

Oct 3, 2022

Amazing course!

By Raspiani

Aug 28, 2021

Awesome Thanks

By 莫毅啸

Dec 24, 2021

haved fun!


Sep 29, 2021

Nice !!!!

By Naveen K

Nov 23, 2022


By Vijay

Nov 20, 2022

What's Good

- The selection of the topics for the programming assignments is outstanding - I am very experienced at completing QwikLab assignments with ML Pipelines and I still learned something new.

- The topic coverage is great - I learned a lot of things in the field that I was not aware of.

What can be improved

- The lectures are being read from notes and it's hard to listen to without increasing the playback speed to 2x. I think there should be more readings and the videos should be more engaging (i.e. like the GAN specialization's lectures).

- The quizzes should count as part of the grade. It's possible to complete the all QwikLab assignments within a couple hours and the entirely of the course completion credit is based on that.

By Fernando F

Mar 9, 2022

Very nice course. The reason I graded it as 4 (and not 5) was related to the educational value of the labs based on Google's console. Per se, the exercises were flawless but I felt like I was just running the steps without much understanding of what I was doing.

Yet, an awesome course. I learned a lot! Thank you very much!

By Carlos A L P

Jan 3, 2022

Great course, you can learn new concepts related to MLOps and new technologies like major Cloud vendors, packages and platforms like TensorFlow for the ML model. I would like to have more exercises to apply the various terms and processes seen during the course

By anand v

Aug 31, 2022

It covers a vast territory of material. However, there is plenty to learn in terms of concepts. Some of the graded labs can make you dizzy. Overall, it is worth the effort. Get a financial waiver if possible.

By Ioannis A

Jun 15, 2022

There were a lot of useful information and practical insights about the subject of the course. The material on Tensorflow-specific modules felt a bit unorganized and cumbersome to go through.

By Jerry Z

Apr 4, 2022

Lots of hands-on exercises accompanying knowledge learned in this course 3, but could be difficult for someone without prior working knowledge on Google Cloud platform/services.

By Suet Y M

Jun 8, 2022

The assignments are just quizes, and no practical programming exercise

By Ruan L D

Nov 19, 2021

Good but I think that is much content for low time