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

4.5
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1,503 évaluations
161 avis

À propos du cours

Want to know how you can improve the accuracy of your ML models? What about how to find which data columns make the most useful features? Welcome to Feature Engineering where we will discuss good vs bad features and how you can preprocess and transform them for optimal use in your models....

Meilleurs avis

GS

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.

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.

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26 - 50 sur 161 Avis pour Ingénierie des fonctionnalités

par KAMASANI V R

Jun 22, 2020

This course helped me in exploring the google platform in terms of data visualization, feature engineering techniques etc. Thank You.

par 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.

par Meynardo J

Jul 28, 2018

Very good stuff on feature engineering overall. Feature cross was new to me and looked very promising, and tf.transform was awesome.

par Omar M

Mar 23, 2020

very intresting and insightful ideas about data preprocessing and a great introduction to different tools to execute pipelines.

par 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!!

par Anupam S

Dec 02, 2019

Detailed explanations and examples. At places the explanations and intertwined topics do get convoluted, but overall good.

par Harold M

Sep 26, 2018

Excellent course! One of the most important in this specialization.

I learned a lot!

Thank you very much Google Team!

par Sri B

Aug 15, 2019

Being a beginner I felt very difficult to understand concepts taught in this course.But the content was awesome

par Wayne R

Aug 07, 2019

This course definitely shows the value of the GC and TF tools and provided insight into building ML systems

par kai w h

May 25, 2020

Really Good! I learnt so much! I'm really thankful for having such a great teaching team. thank you!

par Mark B

Dec 26, 2018

Very useful. Good job.

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

par Juan P D P

Aug 31, 2018

A highly sofisticated course about feature engineering and tensorflow union with tf.transform.

par Aditya h

Aug 14, 2018

Best course in the series so far! liked the labs, a bit heavy and challenging at the same time

par Hua S

Mar 11, 2019

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

par Stephen P

Jun 14, 2018

Very informative, however in part 5 (iirc) the lab did not match up with the summary video

par Wolfgang G

Jul 22, 2018

Very, very comprehensive deep dive into the "real" stuff. tf.transform truly rocks, guys!

par Sanjay K

Jun 06, 2018

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

par Gustavo M

Aug 27, 2018

Probably the most important part of the specialization, and where I learned the most

par Badhan S

May 01, 2020

I like this course very much. It saves me a lot of time about features selection.

par 서영웅

Oct 24, 2018

If you want to become AI and Data Engineering jobs, It is really helpful for you.

par Ilias P

Nov 02, 2018

It was the most difficult from all 4 until now, BUT it was worthing the effort!

par Morris C

Oct 28, 2018

It worth to take 2nd times for practice in real world ML feature engineering.

par Nir P

Mar 08, 2020

Excellent course. Explained very clearly. Have examples on how to do things.

par Fedric

Feb 03, 2020

Had some problems with a few of the labs but the course was very informative

par Gary T

May 30, 2019

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