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

4.3
stars
808 ratings

About the Course

In the second course of Machine Learning Engineering for Production Specialization, you will build data pipelines by gathering, cleaning, and validating datasets and assessing data quality; implement feature engineering, transformation, and selection with TensorFlow Extended and get the most predictive power out of your data; and establish the data lifecycle by leveraging data lineage and provenance metadata tools and follow data evolution with enterprise data schemas. 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: Collecting, Labeling, and Validating data Week 2: Feature Engineering, Transformation, and Selection Week 3: Data Journey and Data Storage Week 4: Advanced Data Labeling Methods, Data Augmentation, and Preprocessing Different Data Types...

Top reviews

SC

Jul 2, 2021

Interesting material. There are quite a lot of typos and many code snippets are directly from the tfx manual pages however the instructions provided and logic of the course is clear.

DD

Jul 20, 2023

Liked it for the most part. It was a bit dull when going over the details of schema updates and meta data. But that might be the nature of the beast.

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76 - 100 of 166 Reviews for Machine Learning Data Lifecycle in Production

By Carlos D A D Á

Nov 23, 2022

Really useful and interesting.

By Shannen L

Jul 29, 2021

very helpful for ml engineers

By Bonginhlanhla M

Sep 2, 2023

The course was really great

By Shan-Jyun W

Jan 15, 2022

Great course! Very Useful!

By RISHABH S

Jul 22, 2021

Great practice exercises!

By BRAMWEL O

Sep 14, 2021

Great hands-on learning.

By John M

Apr 14, 2023

I love this course!

By Kamran S

May 25, 2022

very informative

By Don K

Jun 9, 2021

Fantastic course

By Raspiani

Aug 19, 2021

Great, Thanks..

By Carlos S

Jan 10, 2024

Perfect !!!!!!

By Manuel T

Oct 20, 2023

Very well done

By Vu V D

Oct 16, 2022

Useful course!

By Harjeet S Y

Oct 25, 2023

superb course

By EMO S L

Sep 20, 2021

Great content

By Viktor K

Aug 4, 2021

Wonderfull!!!

By oyenola p

Nov 26, 2022

Great Course

By Charles A N

Mar 12, 2024

Very Good

By Fernando E M M

Aug 4, 2023

Fantastic

By Justin H

Aug 5, 2023

Brutal.

By USEYD K

Dec 29, 2022

love it

By Mohsen M

Aug 19, 2023

great

By Jennifer K

Dec 17, 2021

This is a very thorough introduction to data issues that arise when you go from proof-of-concept to project in production. It uses TensorFlow Extended components to illustrate workflow concepts, and the labs involve using these components in programming assignments. If you do all the ungraded labs, the programming assignments are quite easy.

By Dennis M

Aug 13, 2022

This course was interesting. However it did dive into the software side of the data life cycle. Not as much discussion was provided to accomplish the graded assignments. The ungraded labs did help, but did not provide enough depth in places. I would have liked to see more of the architecture of the entire data lifecycle solution presented.

By Ivan P

Nov 23, 2021

To much emphasis on tensorflow, too few on underlying concepts, while we need it and alternative to TF. If the course was call "implementing <current course name> in TF" this would be fine, otherwise name is mileading. However, the course content is well structured and interesting, just 4 stars for a misleading name :)