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Machine Learning Modeling Pipelines in Production(으)로 돌아가기

deeplearning.ai의 Machine Learning Modeling Pipelines in Production 학습자 리뷰 및 피드백

4.6
별점
129개의 평가
23개의 리뷰

강좌 소개

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...

최상위 리뷰

JS
2021년 9월 13일

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

MB
2021년 10월 20일

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.

필터링 기준:

Machine Learning Modeling Pipelines in Production의 27개 리뷰 중 1~25

교육 기관: Folkert S

2021년 9월 18일

I thought this course was ok. On the one hand, the theory that is taught is quite general and trivial, while on the other hand, the technical focus is mostly on Google's tools and deep learning. As getting machine learning to production is an advanced task and requires a broad set of skills, I would've, for instance, expected this course to be more on structured data. Also, most of the labs, especially the GCP ones, feel just like copying and pasting some commands, it's not that challenging and therefore I didn't learn a lot there.

교육 기관: Cosmin K

2021년 8월 16일

Great material, insigthful notebooks and a valuable review of numerous concepts and tools! The course set me on track with steps to take and pitfalls to evoid. Thank you! Now is practice and continous learning from my part.

교육 기관: Thành H Đ T

2021년 8월 24일

wow, Its very good

교육 기관: Peter W

2021년 8월 9일

Covers a lot of content at a high level. One slight criticism is that the graded exercises focused on Google cloud and didnt require much thought. The ungraded labs on the other hand were quite interesting.

교육 기관: Hieu D T

2021년 8월 15일

A bit dependent on GCP, took me quite a decent amount of time to do network setting. You should use your own internet, do not use one behind corporate proxy like I did. Materials and guides are great.

교육 기관: Ashwani K

2021년 8월 7일

Some of the topics were too advanced and instructor assumes that we know those basics. It felt rush through little bit and more of reading slides then explaining at many places

교육 기관: Andrei

2021년 9월 9일

need to improve the explanation of topics

교육 기관: Yixin D

2021년 10월 13일

I find this course extremely hard to follow, some main and tricky concepts are only covered by a mere sentence in the lecture.

교육 기관: Roger S P M

2021년 9월 5일

So Boring!

교육 기관: Hitesh K

2021년 7월 18일

So far the most informative course in this specialization. This course has actually taught me how different is ML in production than doing simple Ml stuff on notebook for academic or research purpose. You get to see the bigger picture, i.e, different and bigger constraints that needs to be addressed for deploying any model to be on systems, specially edge devices.

교육 기관: Jonathan S R P

2021년 9월 28일

I strongly recommend this course to anyone interested in MlOps and how to manage a ML pipeline in production, i learn a lot about pipelines, distillation and interpretable models. Can wait to put all this knowledge in practice :)

교육 기관: Umberto S

2021년 8월 29일

Great course! One of the most clear and extended courses by DeepLearning.ai. I think It covers in an excellent way all topics to understand what MLOps is and how to approach it in the right way.

교육 기관: Jitendra S

2021년 9월 14일

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

교육 기관: Melanie J B

2021년 10월 21일

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.

교육 기관: Nhan N L

2021년 9월 21일

This course is helpful. Enrich my knowledge with data concepts, optimal high-performance model tools and model debugging.

교육 기관: Mario T

2021년 9월 5일

Outstanding! Exceptionally informative. Makes me look way aheady how to implement ML pipelines, and how to analyze them.

교육 기관: vadim m

2021년 8월 4일

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

교육 기관: Reza M

2021년 9월 14일

T​his is very helpful course to understand the life of model specially after its deployment.

교육 기관: Cees R

2021년 10월 15일

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

교육 기관: amadou d

2021년 8월 8일

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

교육 기관: Kiran K

2021년 7월 22일

Good But More practical needed with theory

교육 기관: Fernandes M R

2021년 9월 24일

The first course of MLOps, and the best.

교육 기관: Илья В

2021년 9월 9일

great course, a lot of stuff

교육 기관: Liang L

2021년 7월 22일

Good content and hands on.

교육 기관: Raspiani

2021년 8월 28일

Awesome Thanks