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学生对 Google 云端平台 提供的 特色工程 的评价和反馈

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1,231 个评分
120 条评论

课程概述

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 <<<...

热门审阅

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.

BR

Jan 10, 2020

i really like the effort taken in developing this course, the structure. Kudos to Laks for converting lots of statistical and coding language to very simple understandable english.

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76 - 特色工程 的 100 个评论(共 120 个)

创建者 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

创建者 Wang Y

Oct 07, 2018

Nicely explained concepts with real world examples! Could have explain more about the code and the meaning behind some of the qwiklabs.

创建者 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...

创建者 Keith H

Sep 01, 2019

Love the course but this specialization is fairly complex and is new type of thinking as such take a bit of understanding.

创建者 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.

创建者 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.

创建者 Frederik C

Nov 18, 2019

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

创建者 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

创建者 Attila B

Dec 08, 2018

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

创建者 Emily T

Jul 05, 2019

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

创建者 Sandeep K

Jul 30, 2018

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

创建者 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

创建者 borja v

Jun 21, 2019

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

创建者 Alexander Z

Dec 29, 2018

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

创建者 Marcos H

Nov 08, 2018

Very practical and Lak is a great teacher and communicator!

创建者 Joel M

Dec 06, 2018

good clear instructions, and valuable content.

创建者 Anupam P

Aug 26, 2019

Comprehensive yet precise and clear.

创建者 Rohit K A

Dec 24, 2018

No course material for reference

创建者 Rahul K

May 05, 2019

Lovely Course. Thanks Google

创建者 Ripunjoy G

Nov 21, 2019

Labs have problems

创建者 Terry L

May 01, 2019

개요를 알게 되서 좋음

创建者 Ahmad T

Aug 27, 2019

Great

创建者 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.

创建者 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.

创建者 Jonathan A

Aug 27, 2018

The concepts were taught well. However, a lot of code and cloud interaction was involved, making the labs a key piece of the material. Two of the labs didn't work because the Google lectures aren't up-to-date with the Google APIs. Although Coursera response to the bad labs was prompt, the Google team did not respond.