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Avis et commentaires pour d'étudiants pour Ingénierie des fonctionnalités par Google Cloud

1,414 évaluations
149 avis

À propos du cours

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: <<<...

Meilleurs avis


Apr 09, 2020

This course covers a lot about the data pre-processing, and the tools available in Google Cloud to enable the gruelling tasks. Thanks very much for the lectures and training labs. Very informative.


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.

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101 - 125 sur 150 Avis pour Ingénierie des fonctionnalités

par Gregory R G J

Jan 30, 2019

Thumbs sideways.

I learned a ton but it appears as technology grows and changes updates to the platform is sort of static.

par Zezhou J

Nov 09, 2018

The content is quite rich in this course. I feel decomposing it into two weeks might make it structurally more clear.

par Frederik C

Nov 18, 2019

Very well explained, lost time during tutorials because of apache beam version conficts with google cloud dataflow

par Roberto T C

Jan 11, 2020

starts off with a bang, and generally excellent. the tf.transom section needs a bit of freshening and refocusing

par Vamsi K B

Mar 11, 2020

This course gives an ample understanding on the significance of Features and Data in Machine learning.

par Attila B

Dec 08, 2018

Really comprehensive course.Was a bit tough to follow sometimes,but guess it's just beginners problem.

par Emily T

Jul 05, 2019

This course really needs more hands on work with code, but it was still good and I learned lots.

par Sandeep K

Jul 30, 2018

this was really good, except removed one start for trifacta integration of dataflow lab.

par Nagireddy S R

Dec 13, 2018

Felt like it was cut short at the end. Would like to see a bit more on the tf.transform

par borja v

Jun 21, 2019

the course needs some code upgrades because of ML engine is close to be depecreated

par ThemisZ

Feb 04, 2020

very nice course , -1 star for no pdf/ppt notes made available

par Alexander Z

Dec 29, 2018

great content and cool notebooks ... sometimes hard to follow

par Marcos H

Nov 08, 2018

Very practical and Lak is a great teacher and communicator!

par Fernandes M R

May 15, 2020

Maybe a little more example of how deal with features.

par Malithi N

May 25, 2020

This course explains theories nicely with labs

par Joel M

Dec 06, 2018

good clear instructions, and valuable content.

par Anupam P

Aug 26, 2019

Comprehensive yet precise and clear.

par Rohit K A

Dec 24, 2018

No course material for reference

par Rahul K

May 05, 2019

Lovely Course. Thanks Google

par Ripunjoy G

Nov 21, 2019

Labs have problems

par Terry L

May 01, 2019

개요를 알게 되서 좋음

par Benjamin F

Apr 08, 2020


par Ahmad T

Aug 27, 2019


par Yingchuan H

Sep 17, 2018

The content of this course might be a bit too much for one week compared to previous courses in the specialization. Also, it would be great if some of the labs are more clarified and introduce more opportunities for students to participate in writing code for the lab session rather than just going through it and running existing code. I did experience some issues installing the tf transform package for the last lab, which might not be a common issue, but was kind of frustrating as it prevents me from more exploration of the learned skills. Thanks for providing the course anyway. I learned a lot from it.

par Fabrizio F

Aug 06, 2018

The subject is very interesting and I was alwyas curious about how Feature Engineering should be done with Tensorflow. I come from Pandas, where feature engineering is not that difficult, but with Tensorflow it is different and not that intuitive. Here in the course three different ways are presented. I guess I'll have to study more Apache Beam.