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Learner Reviews & Feedback for Recommendation Systems on Google Cloud by Google Cloud

4.5
stars
469 ratings

About the Course

In this course, you apply your knowledge of classification models and embeddings to build a ML pipeline that functions as a recommendation engine. This is the fifth and final course of the Advanced Machine Learning on Google Cloud series....

Top reviews

DL

Aug 19, 2019

I enjoyed this course too much, usually every company wants a recommended system, but the courses or examples available on the web are few. Very well explained many theoretical aspects.

JA

Mar 25, 2020

Amongst all tensorflow courses this is probably the most useful. Using AI to make better and automated recommendations can benefit most businesses.

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76 - 84 of 84 Reviews for Recommendation Systems on Google Cloud

By KyleGHan

Jan 11, 2020

good

By Ben

Jan 21, 2021

Pros:

Doesn't rush over the various methods, discusses them in detail. The lab videos are some of the most in depth in this specialization.

Discusses the logic of designing a good recommender system quite well.

Cons:

The content is out of date in applications. Like it seems every course in this spec, the tasks we are assigned and the tasks discussed are totally mismatched a lot of the time.

By Ulrich K

Jan 25, 2024

The quality of the course got worse towards the end: to much speach with few content in recommender systems, many unfcuntional notebooks.

By Abraham T

May 30, 2021

The Qwiklabs materials are outdated, however the lectures are insightful.

By Kai W

Jan 17, 2022

Outdated (TF, GCP)

By Aldrich L

Oct 25, 2021

The first part on content-based systems was pretty good, but everything after that was a mess. The second instructor (Ryan) was talking way too fast, and it felt like he was rushing everything he was explaining, and it would've been alright if his explanations were, at least, comprehensive enough. The problem is, there wasn't much groundwork in the course to build a good foundation for the students; they just did a brief introduction to the concepts, then rushed through the code implementation. Slowing down the videos did not help at all; it actually made it worse. The labs are another story, but then everyone else seems to be complaining about that, as well.

This is the only course in both specializations (ML on GCP and Advanced ML) that I didn't like.

By Walter H

Jun 6, 2021

while the topics and lectures are very interesting, the course is extremely broken in its current form. There are multiple instances where you first get a lecture and are then asked to do a lab, but the lab is on a completely different topic than the lecture was. One example is the final lab of week 2, where you should be building an end to end solution, but instead you get a lab that only focusses on a topic from week 1. It seems this course was reworked at some point, but the 2nd version is no longer coherent whatsoever. It's hard to recommend this course in its current form as a result.

By Nghị N Đ

Aug 1, 2023

The organization and content were unclear and repetitive. The reinforcement section was tedious with too much theory and lacked practical application. The labs using TensorFlow were not suitable for beginners. Improvement is needed for a better learning experience.

By Alex M

Jan 5, 2023

My first one-star course on coursera which is especially disappointing given that it is a course from google. It is also a pity since the covered topics and approaches are very interesting. The main problems are: simpler methods are overcomplicated (first week) and more complicated approaches (week 2) are severely lacking math (especially RL). But the worst thing is the labs and how they are organized. They are simply unpleasant to do, and the code there is UNREADABLE and boring.