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Вернуться к Machine Learning Modeling Pipelines in Production

Отзывы учащихся о курсе Machine Learning Modeling Pipelines in Production от партнера

Оценки: 233

О курсе

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...

Лучшие рецензии


13 сент. 2021 г.

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


20 окт. 2021 г.

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.

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26–45 из 45 отзывов о курсе Machine Learning Modeling Pipelines in Production

автор: amadou d

8 авг. 2021 г.

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

автор: Daniel W

9 июня 2022 г.

Great course, probably the best in the specialisation.

автор: Fernandes M R

24 сент. 2021 г.

The first course of MLOps, and the best.

автор: Thiago P

1 февр. 2022 г.

Really liked the last week content

автор: MORUFU B

14 мая 2022 г.

This is a very detail course

автор: Илья В

9 сент. 2021 г.

great course, a lot of stuff

автор: Liang L

22 июля 2021 г.

Good content and hands on.

автор: Raspiani

28 авг. 2021 г.

Awesome Thanks

автор: 莫毅啸

24 дек. 2021 г.

haved fun!

автор: EMO S L

29 сент. 2021 г.

Nice !!!!

автор: Fernando F

9 мар. 2022 г.

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!

автор: Carlos A L P

3 янв. 2022 г.

G​reat 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

автор: Ιοannis A

15 июня 2022 г.

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.

автор: Jerry Z

4 апр. 2022 г.

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.

автор: Suet Y M

8 июня 2022 г.

T​he assignments are just quizes, and no practical programming exercise

автор: Ruan L D

19 нояб. 2021 г.

Good but I think that is much content for low time

автор: Nithiwat S

29 июня 2022 г.

Just like the previous course in the specialization by the same instructor. He bascially reads from slides with little to no explanation. He barely explains any concepts, gives examples to help develop understanding. Some concept is unclear and poorly explained. Every single lecture, he just reads from scripts. It's very frustrating to learn. Coursera, in my view, is strong in delivery content that's more technical, more engaging, better explained technical concepts. But this course fails to deliver that. Watching many videos on Youtube is better than learning from this instructor. It is just terrible delivery, and I wish it was Andrew Ng who taught it. The only good part is the labs. Labs are well prepared and help with the study.

автор: Arturo M

26 июня 2022 г.

I'm a big fan of Andrew Ng's ML courses. However, I'm very dissapointed with this one, for several reasons.

First, the instructur is not nearly as engaging as Andrew Ng himself. Most of the time he basically reads through the slides in a monotous way.

Second, the course tries to cover too many concepts. Instead of selecting a few core topics and explaining them in detail, the course seems like an ennumeration of ML concepts. Most of the times, the explanations are way to shallow to be of practical use.

Third, the exercises are quite poor. Most of them are just plain Google Cloud tutorials on Quicklabs.

автор: Sagar D

15 июня 2022 г.


автор: Longlong F

27 мая 2022 г.

In the C3W3 lab, the status of the pods never change to 'running'. I had to re-do it many many times and but still didn't get the score. I am really sick and tired for these course. never again.