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Отзывы учащихся о курсе Проектирование признаков от партнера Google Cloud

4.5
Оценки: 1,185
Рецензии: 115

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.

TY

Sep 23, 2019

Feature engineering is important but less discussed compared to general ML or DNN. Feature cross is a new concept and yet very useful for dealing with large datasets.

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1–25 из 115 отзывов о курсе Проектирование признаков

автор: Stephen R

Aug 27, 2018

A lot of the code, did not work.

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: Martin A K

May 31, 2019

Would appreciate more guidance on the exercises

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: 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.

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: Omar M A

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.

автор: Abdul R Y

Nov 28, 2018

Great Course!

автор: Mark B

Dec 26, 2018

Very useful. Good job.

Hands-on parts could be broken into smaller chunks with longer de-briefs.

автор: Mario R

Jan 13, 2019

This course should be mandatory for any ML practitioner. It teaches you that ML is not only about throwing whatever you want to (sort of) a model and expect to get reasonable results. It is about getting to know your problem and squeeze the data available.

автор: Putcha L N R

Jan 13, 2019

Amazing course! Gives insight into one of the most important part of solving Machine Learning problems; feature engineering!!

автор: SULTHAN M N

Jan 18, 2019

had a great experience

автор: Eric

Feb 02, 2019

Learned a lot

автор: Sujeethan V

Apr 02, 2019

Great, Labs were redundant at times.

автор: Stephen Y

Apr 06, 2019

Great teaching

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.

автор: Raja R G

Dec 07, 2018

Learned lots of stuff on feature engineering

автор: Hua S

Mar 11, 2019

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

автор: Serhan A

Jun 05, 2018

Great series!

автор: Jun W

May 28, 2018

This course is a little bit harder than the former three courses. But the intuition of feature cross and embedding is very inspiring.

автор: Sanjay K

Jun 06, 2018

Very Detailed and good for individuals who do not have statistical background. Thank you.

автор: Giovanni S

Jun 02, 2018

Great course. A bit more difficult than the other 3, because the topic is more complex. Once finished the course you'll get the big picture. It may take some time to digest all little details, but everything is very well explained in a more than exhaustive way. Teachers are also very engaging and never boring. Highly recommend to anyone interested in the topic!

автор: Vishal K

Jun 18, 2018

Comprehensive Overview on Feature Engg

автор: Carlos V

Jul 01, 2018

Excellent Course and advice from experts about Feature Engineering and data pipelines utilizing advanced processes on GCP, thanks to Google and Coursera.