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Отзывы учащихся о курсе Проектирование признаков от партнера Google Cloud

4.5
Оценки: 834
87 рецензий

О курсе

Want to know how you can improve the accuracy of your machine learning models? What about how to find which data columns make the most useful features? Welcome to Feature Engineering on Google Cloud Platform where we will discuss the elements of good vs bad features and how you can preprocess and transform them for optimal use in your machine learning models. In this course you will get hands-on practice choosing features and preprocessing them inside of Google Cloud Platform with interactive labs. Our instructors will walk you through the code solutions which will also be made public for your reference as you work on your own future data science projects. >>> By enrolling in this course you agree to the Qwiklabs Terms of Service as set out in the FAQ and located at: https://qwiklabs.com/terms_of_service <<<...

Лучшие рецензии

OA

Nov 26, 2018

It's a pretty interesting course, specially that's the only one that teaches featuring engineering with a focus on production issues, but it assumes some knowledge with apache beam, and dataflow.

P

Mar 07, 2019

The content is great, not just from a technical point of view but for all the know-how that the different instructors share during in the videos and labs.

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1–25 из 91 отзывов о курсе Проектирование признаков

автор: Yasim K

Sep 12, 2018

The tf.transform and Apache Beam concepts are not explained in simple ways.

Also the lab jumped from simple programs to complex programs.

автор: Stephen R

Aug 27, 2018

A lot of the code, did not work.

автор: Sudesh A

Jul 28, 2018

The videos are good and better than the last two courses in the specialization; however, the labs lack proper instructions and not that helpful. This course seems like more of an advertisement for Google Cloud Platform than feature engineering: details of engineering part is hardly covered in the course; more emphasis is on demonstrating on how to do it on GCP.

автор: Ian M

Jul 27, 2018

Had a lot issues with the quiz grader.

автор: Robert U

Jun 11, 2019

The assessments do not actually require writing any code; you just execute the given code blocks. Little knowledge will be retained unless students actually write code and solve problems, even for the motivated ones who read through all the given code.

автор: Martin A K

May 31, 2019

Would appreciate more guidance on the exercises

автор: Gary T

May 30, 2019

Every aspiring Data Scientist or data analyst MUST take this certification!!

автор: Nayanajith P

May 28, 2019

It's nice

автор: Fathima j

May 09, 2019

great course and very intrsting

автор: Rahul K

May 05, 2019

Lovely Course. Thanks Google

автор: Terry L

May 01, 2019

개요를 알게 되서 좋음

автор: Filbert K

May 01, 2019

Thank you.

автор: Woojin J

Apr 30, 2019

nice & fun

автор: 영신 박

Apr 29, 2019

Awesome!

автор: Maheboob P

Apr 21, 2019

faced multiple issues

a)Qwiklab wasnt allowing to login with error that said "account is locked"

b) labs were not as interesting as others

автор: Bill F

Apr 20, 2019

Excellent course, great trainers.

автор: Francois R

Apr 17, 2019

Very interesting theory, shows the power of Tensorflow in the field. I had trouble with the last lab though, which when I ran it step by step, would block my qwiklab account because of resource limitations...

автор: 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.

автор: Marko H

Apr 06, 2019

Basically this course would receive four stars, but repeated problems with qwiklabs had a severe impact on my overall experience. I got thrown out three times in a row (and my account locked) during dataflow lab.

Every time I had to request unlockin of my account, which took half a day every time. When requesting advice to avoid this error, I got offered the general and vague explanation that I "should only use the resources required by the lab". I am 100% sure that I didn't use any extra resources, including zones and regions.

The Coursera's helpdesk went behind the excuse that Qwiklabs is a third-party service. That may be the case, but since Qwiklabs has been integrated into the Courseras' course, the ultimate responsibility lies with Coursera.

I hope that Coursera will co-operate with Qwiklabs to sort out this very annoying problem.

автор: Stephen Y

Apr 06, 2019

Great teaching

автор: Sujeethan V

Apr 02, 2019

Great, Labs were redundant at times.

автор: Said A

Mar 22, 2019

A separate course to emphasise the role and importance of feature engineering in machine learning is what really got to me. With examples and explanation how your model can improve with feature engineering did the trick. Before, it was just a note in my notebook. Now, I really understand the importance of it.

However, having said that, the course could have been much shorter. It feels like, these courses are Google way of promoting its ML Cloud services.

автор: Harm t M

Mar 13, 2019

This was hard. Not directly applicable to where I am in my machine learning career, but good to know in the future, nonetheless...

автор: Hua S

Mar 11, 2019

Hope all the materials in this course will be updated soon. However , thanks to all of you!

автор: Patxi G

Mar 07, 2019

The content is great, not just from a technical point of view but for all the know-how that the different instructors share during in the videos and labs.