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Avis et commentaires pour d'étudiants pour Serverless Machine Learning with Tensorflow on Google Cloud Platform par Google Cloud

4.5
stars
2,524 évaluations
305 avis

À propos du cours

This one-week accelerated on-demand course provides participants a a hands-on introduction to designing and building machine learning models on Google Cloud Platform. Through a combination of presentations, demos, and hand-on labs, participants will learn machine learning (ML) and TensorFlow concepts, and develop hands-on skills in developing, evaluating, and productionizing ML models. OBJECTIVES This course teaches participants the following skills: ● Identify use cases for machine learning ● Build an ML model using TensorFlow ● Build scalable, deployable ML models using Cloud ML ● Know the importance of preprocessing and combining features ● Incorporate advanced ML concepts into their models ● Productionize trained ML models PREREQUISITES To get the most of out of this course, participants should have: ● Completed Google Cloud Fundamentals- Big Data and Machine Learning course OR have equivalent experience ● Basic proficiency with common query language such as SQL ● Experience with data modeling, extract, transform, load activities ● Developing applications using a common programming language such Python ● Familiarity with Machine Learning and/or statistics Google Account Notes: • Google services are currently unavailable in China....

Meilleurs avis

NP

Jan 09, 2018

Thank you very much for making this course available on Coursera, I cannot agree more the knowledge of Mr Venkat. This is a great way to help people to get started with Google Machine Learning.

HM

Sep 08, 2018

A very good course on TensorFlow, ML and Google MLE on GCP.\n\nThe Labs are self contained and the problems proposed are very challenging. I learned a lot on this course.\n\nThank you!

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201 - 225 sur 299 Avis pour Serverless Machine Learning with Tensorflow on Google Cloud Platform

par Armindo C

Dec 07, 2019

Good course overall but some labs were not working correctly

par Joachim H

Nov 03, 2018

Very good overview of Tensorflow for Data Engineers.

par Anuvrat K

Feb 22, 2019

Nice Content and nice explanation by Lak. Loved it.

par Dmytro C

Aug 25, 2019

It would be much better if there was more quizzes.

par Sam K

Apr 23, 2018

Quite a long course, audio needs some work.

par Jonathan G

Oct 24, 2017

A lot of detail to absorb in a short time.

par Simon P

Dec 09, 2019

Would have prefer to learn with TF2.0

par Narasimhan R

Jun 27, 2017

Very good intro to TensorFlow on GCP.

par Suneel S

Feb 08, 2019

good course, nice practical examples

par NIKHIL P M

May 13, 2019

Good Course For Beginners on GCP.

par Tom M

Feb 18, 2018

Great TensorFlow Examples

par Bhaskar V

Aug 17, 2019

Informative and detailed

par Mariano P G N

Feb 14, 2019

Problems with the lab 7

par Dan G G

Sep 17, 2018

Need a subtitle review.

par Cameron S B

Feb 20, 2019

Excellent course.

par Camilo G

Mar 08, 2019

Useful course

par José C C C

Dec 18, 2019

buen curso

par Luiz T

Feb 26, 2019

Good!

par Ashwin S

May 28, 2019

good

par Girish P

Dec 13, 2017

.

par Veronica G

Nov 30, 2019

Labs have issues, they cannot be followed and/or cannot be scored either. I opened a case with QwikLabs for Lab1 because the Lab gets stuck with an error in Datalab. Lab 7 also has issues:

On Lab 7 : Not a good Lab, sorry, but that's what I think. It seems as if nobody tried it lately. First, the points are based on steps that do not exist, like "Launch Cloud Datalab", so it's impossible to get any score. Secondly, the Lab does not say that it has to be a single-region bucket to create, until we see it in the Notebook, but it also has to be us-central1 (default) region, because otherwise, some steps in the lab will complain that region is not set in the command and that us-central1 region will be used. Thirdly, the Lab says to use Tensorflow 1.x but that is not available anymore; the options are either Tensorflow 1 Enterprise (which launches a jupyterlab instance that is not named tensorflow_****) or Tensorflow 2.x which will launch an instance called tensorflow_****, but with this one, as soon as we start working with JupyterLab, it's error after error in almost every single step. I was unable to do this lab.

Hopefully somebody can follow the labs and help with the issues. I do not think it is good that each of us have to individually open a case with Qwiklabs to get them solved. Somebody from Coursera-GCP, I think, should be following up these issues, reviewing these labs and help with the issues as a focal point, that would be better than having us all opening individual support cases and then post the solutions to the team. We do a lot of other things during the day, and we might miss a deadline or not be as responsive as somebody who is in charge of this learning platform.

par Juan P

Nov 23, 2019

Course is an ok introduction to ML with Tensorflow. It does however needs a serious face lift when it comes to the labs. Several where broken and required debugging and some intuition to work around the bugs in order to finish them and get a grade.. If you want to learn Tensorflow, I would look elsewhere, if you want a quick course where you want the very basic and do not mind the hands labs being broken (i.e. just care about the very high level information), then sure, go ahead and enroll

par Alexander A

Dec 30, 2019

The content was interesting and relevant, but most of the "labs" amounted to clicking through a pre-defined Jupyter notebook. I would not consider that to be interactive training and calling them "labs" is misleading - they might as well have been slides or videos. Also, in Dec 2019, the age / updates of this material are showing - some of the edits were not careful and there are abrupt stops to videos as well as mismatches between what is shown and what the notebooks do.

par Francisco A D Z

Mar 15, 2019

El RSME inicialmente se fijo en $8 dolares.

Al final utilizando el metodo con Ingenieria quedo menor a $4.

Me quedo la incognita de como es posible que con los metodos intermedios pueden ser tan inexactos casi un 50% de error con respecto al valor esperado? En la vida real eso se traduce a millones de dolares en perdidas utilizando herramientas de Google Cloud Platform.

par Josh J

Sep 01, 2017

Course content is excellent. Organization is not good. It seems like there were some errors in the order of a few quizzes as well as links to the wrong sections. If you take this course and find yourself lost on a quiz or a lab; skip it watch more content, then go back. It was probably out of order.