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Learner Reviews & Feedback for How Google does Machine Learning by Google Cloud

4.6
stars
4,711 ratings
727 reviews

About the Course

What is machine learning, and what kinds of problems can it solve? Google thinks about machine learning slightly differently -- of being about logic, rather than just data. We talk about why such a framing is useful for data scientists when thinking about building a pipeline of machine learning models. Then, we discuss the five phases of converting a candidate use case to be driven by machine learning, and consider why it is important the phases not be skipped. We end with a recognition of the biases that machine learning can amplify and how to recognize this. >>> By enrolling in this specialization you agree to the Qwiklabs Terms of Service as set out in the FAQ and located at: https://qwiklabs.com/terms_of_service <<<...

Top reviews

JT

Nov 06, 2018

Great to know how to do machine learning in scale and to know the common pitfalls people may fall into while doing ML. Provides great hands-on training on GCP and get to know various API's GCP offers.

PB

Mar 21, 2019

Really easy with all instruction.I didnt feel bored at any point gave me the basic idea of what is machine learning and how easy google made API's and cloud platform for machine learning\n\nThank you

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501 - 525 of 719 Reviews for How Google does Machine Learning

By Anubhav S

Jul 24, 2019

I am a student at a college and for me, this course makes a nice start. Although I find some things to be quite far fetched i.e some keywords we hard to understand.

I did understand the business aspect of this course and save it for my future years. This course makes me hype about the further one

!!

By Javier C

Aug 19, 2018

Good essentials and introduction to Machine Learning. It doesn't go in depth of math behind, instead, it keeps it in a low level explanation for understanding basics of ML. They introduce how Google's APIs may be used for ML, and they seem really easy to use and get with them in production.

By Joshua B

Sep 11, 2019

I enjoyed the theoretical discussions, including the full process discussion, surrounding ML. Realizing that ML is not a panacea for random problems was a game-changer in focusing our efforts on problems that could benefit from ML now and defining the requirements for ML on other projects.

By Vishal V

Nov 03, 2018

A well put out course. The content flow was great and the Google product info seemed more contrived than ads. The lessons could have been a little more detailed and the content split into 2 weeks or so. A good course if you take it after Andrew NG's Structuring ML Projects course

By Saibal M

Jun 13, 2019

It's a part of the specialisation, so taking this course is important for completing the specialisation. But the contents of course is also important for a beginner, who is just going start his/her career in ml. It teaches some useful key points on doing ml in real life.

By Shridhar H

Jun 30, 2018

The course was excellent. It cleared some myths about Machine Learning. I always though that training the ML model was important but collecting data is much more important than that.Looking forward to use Google Cloud Platform in the future for production of my projects.

By Sinan G

Aug 03, 2018

Interesting new insights about biases in ML and a little about how to avoid it, thus going towards so-called "inclusive" ML. Nice overview about how to frame an ML problem and the key importance of data. Good and quick review of some of the Google Cloud API services.

By Ashutosh G

Aug 03, 2019

With focus on how to implement ML in the real world the course provides us with at least one part of the ML Pipeline which can allow an organization to quickly implement ML in its business. I look forward to the data ingestion part of the specialization.

By Nagaraj S

Dec 29, 2018

Excellent material on what are the pitfalls to avoid while doing machine learning. The laying groundwork and following all the steps section made sense. It shows that the course material has been prepared by practitioners - they "know their stuff".

By Jayank M

Jul 06, 2018

At some points it was a bit confusing. Especially the labs, where some instruction were not at easy to understand as the could be. But overall I found this course very helpful in understanding what ML meant and how we should approach it.

By Zhenyu W

Jan 02, 2019

Overall the course is good. IMHO the quiz needs to be improved. It should have more questions and the questions should be more directly related to the lecture or the contents. And I think the course should add some case studies.

By Manohar P

Jan 10, 2020

The information which is potrayed very beautifully.Lecturers are quite clear and gave very isolated information.Finally it is one of my best course on online platform with a lot of basic knowledge on ML with clarifications.

By Rohini M

Apr 20, 2019

Good introduction into Machine learning. Does not tax you with the jargon and deep concepts but more like an outline to how Machine Learning is implemented. Has Qwiklab exercises which helps you get familiar with the tools.

By Jean-Luc D

Nov 22, 2018

Very business-oriented

Large view on state of the art of Machine learning

good support on the Labs

Google culture-oriented

Sometimes difficult to understand for a non-American native (eg : I had no idea of what a slushie was)

By Stanley

Jun 28, 2018

The introduction course by google address the practical difficulties that we come across while developing and deploying ML model . Necessary for any one who would like to put their model in production in scale.

By Gaurav M

Jan 14, 2019

An excellent overview providing a birds-eye view of where ML fits in the larger scheme of a software project and how it evolves. It also provides a good introduction to leveraging Google's ML APIs.

By Jesús O S

Jul 29, 2018

Great course for introduction. Very clean where you get a good first idea of which are the tools used by google to implement ML. Specially loved the Notebooks with the pre-installed programmings.

By Drew F

May 14, 2018

Maybe you could require students to make some changes to the code to make it work, in order to incorporate more student interaction, and thereby more robust learning, into the tasks.

By Cyriac B N

Aug 12, 2019

The course gives insights into business plans and strategies that the google team have put into practice in their products.The examples used to explain concepts were really good.

By Evren G

Jul 05, 2018

Great and thoughtful course content. Labs could be better as they currently don't challenge the student to think. If the labs were improved, this would be a 5 star course.

By Aditya K

May 07, 2018

Pros:

Great overview of tools that may be useful for app developers.

Cons:

Some details were not clear. Too many things to take care of, gcp, datalab, and a myriad of apis.

By Anupam S

Nov 29, 2019

This course is very good. However, before attempting this course you should have taken some basics of maths (Probability) and ML from some other entry level courses.

By John G S

May 25, 2018

Nice introduction; however, it felt like some presenters were attempting to demonstrate their technical prowess. No need for this detail at the early stage.

By hammad z

Sep 08, 2019

Course is pretty basic and gives overview of the google cloud products. Overall i am happy with it. But at times i feel they made it lengthy with no reason

By SAI S K

Nov 26, 2018

It was nice learning this. But some options are not working as mentioned in the content. Like creating Credentials was not always possible in the cloud