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Learner Reviews & Feedback for Machine Learning in the Enterprise by Google Cloud

1,455 ratings

About the Course

This course takes a real-world approach to the ML Workflow through a case study. An ML team faces several ML business requirements and use cases. The team must understand the tools required for data management and governance and consider the best approach for data preprocessing. The team is presented with three options to build ML models for two use cases. The course explains why they would use AutoML, BigQuery ML, or custom training to achieve their objectives....

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The course is difficult. You may need to review some sections because off the amount of information.


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This course tells about the different aspect of usage of art and science in machine learning.

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101 - 125 of 128 Reviews for Machine Learning in the Enterprise

By Phac L T

Aug 1, 2018

It would be nice to have more complex datasets where predictions would be more meaningful.

By Oleg O

Oct 20, 2018

Very good course, but probably requires some more hand-on practice

By Joel M

Dec 12, 2018

good lessons and in depth coverage of a range of issues

By Hugo H

Apr 3, 2020

Good course, pragmatic and full of practical exercises

By Attila B

Dec 20, 2018

Really good course with a lot of practical examples.

By Pratik S

Oct 21, 2019

complete hyper parameters is given in lab

By Ruslan A

Aug 16, 2019

Many notebooks contain some typo/erros.

By Wang Y

Oct 29, 2018

best course in the specialization!!!

By Gaurav B

Feb 13, 2020

I was looking for more hands-on.

By Sarwar A

Feb 23, 2021

Good course overall

By Swaraj P

Mar 10, 2019

Nice tutorial

By Xenon

Nov 11, 2022

Excellent !

By KyeongUk J

Oct 28, 2018


By Matthew B

Jun 29, 2019

Labs were very confusing. Explained theories well but in practice didn't really learn much. I wouldn't recommend if you're a beginner. Google has a very interesting way on teaching.... On that note they should stick to building tech, never teaching. Didn't really learn how to build anything in ML, sort of skimmed on some API's they offer. In reality, the first course was probably the best... The rest of the specialization was just a rinse and repeat sort of thing.

By Bhargav D

Apr 26, 2020

Great course must should make labs compulsory and not provide solution it takes away the fun of thinking.

By Siddharth A

Nov 9, 2018

I felt that hand-on or explanation was not sufficient. Coverage is good.

By Alberto C

Oct 23, 2018

There are some lessons where the concepts are exposed in a too fast way

By Rahul K

May 5, 2019

Some tough concepts !!!

By Yakov F

Oct 18, 2022

All eight labs had defects/ bugs. In four (4) labs the defects prevented me from completing the labs. There was no waiting to contact Google cloud support by chat, but the best the representative was able to do was to give Coursera credit for the unfinished lab, rather than to help find and fix the defect in the lab.

By Pablo I F

Aug 5, 2020

Very bad english subtitles. For non-english speakers, the subtitles doesn't help, but it confuse what the teacher is explaining. It takes me a lot of time to understand some parts of the course

By Mike W

Jun 22, 2019

The notebook based demos are unfortunately pretty useless as labs. All of these courses would be much improved with real labs that require the student to build the system.

By Arman A

Apr 11, 2019

Pros: Tensorflow is an excellent framework for deep learning

Cons :

1- The way this material is designed is 10 X SHIT

2- Either teach properly or don't teach at all.

By Mohannad B

Aug 13, 2020

A lot of inaccurate data, please check deep learning ai specialization for more accurate info. this is good for introducing you to GCP not the concepts of AI

By Ibrahim G

Jun 30, 2024

One of the most low effort things I have seen. The labs don't teach much, as you just go through notebooks, the videos are bad powerpoint presentationas.

By Dakam P

Jan 31, 2024

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