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Volver a Serverless Machine Learning with Tensorflow on Google Cloud Platform

Opiniones y comentarios de aprendices correspondientes a Serverless Machine Learning with Tensorflow on Google Cloud Platform por parte de Google Cloud

4.5
2,441 calificaciones
296 revisiones

Acerca del Curso

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....

Principales revisiones

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.

MG

Sep 21, 2017

Great course! I've learnt a lot. The concepts where super clear. The coding part was a little difficult, I didn't understand all af it, but it's good to have a complete example to use.

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251 - 275 de 290 revisiones para Serverless Machine Learning with Tensorflow on Google Cloud Platform

por 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.

por Alberto C V

Oct 26, 2018

good intro

por Josy

Sep 28, 2018

Willing to rate first couple of courses well for intro. By now expected much more meat - details, coding exercises - not the high level skimming of the tools. Almost an advert for GCP. Anyone with minimum java/python reading level can take this class - no intermediate programming involved.

por Jörn U G

Dec 07, 2019

Good course. Learning experience is mediocre due to many issues in the Lab's .

por Edgar L

Jan 12, 2019

As a person who already knew ML and tensorflow, the way the instructor referred to things, mixed concepts, and simplified some of them, made everything a lot more confusing that it really is. I know its easy to dismiss it in this kind of lessons as "that's a complex subject, so it's normal" but it really comes down to the instructor not being effective as he should be.

por Pavel S

Feb 20, 2019

Although the course is positioned as intro to machine learning with TensorFlow, it includes too many low-level details that you are unlikely be able to conceive without prior knowledge in machine learning and TensorFlow. The parts devoted to feature engineering and hyperparameter tuning are fully chaotic.

por David F

Feb 22, 2019

Muito complexo para quem não tem bagagem algum com python e machine learning.

por Sanjana C

Feb 03, 2019

The course seemed little superficial to me

por Murat T

Jul 26, 2017

Decent content is made very difficult to take in due to poorest editing I have ever seen on Coursera. There may not be many alternatives to this course but in terms of quality this course is not a fair value for money. There are multiple duplications, haphazard cuts, 3-5 second videos that are tied together out of context. It seems the videos are taken from a classroom presentation and shoehorned into an online course format. Very disappointing.

por Dharmesh K

Jul 22, 2017

Organization of the videos is poor. The videos are too many in number and a large number of them are extremely short in duration. But it really good to learn tensorflow and usage in distributed fashion in GCP.

por Darshak S

Aug 02, 2017

Lak is a great teacher, I love his other courses, but this one is not up to the mark. This course has been basically recorded in a live training session and just uploaded the slides and audio as a video.

There are places where he is clearly pointing at stuff on the slide in his live session, but in the video there is no way of knowing what he is exactly talking about.

Please recreate this course from scratch specifically for Coursera format. This is a very important course and students should get all the concepts.

por Prabhu c

Jun 30, 2017

Course Content was good, but poorly organised and span of the videos were very short. Difficult to focus as videos were very short. lot of videos are less than two minutes. Kindly make the videos for atleast 5-10 mins long. If possible, combine the videos, it would help the course takers in future.

por Andriy K

Sep 26, 2018

not practical at all

por Ramón V

May 28, 2019

I'd like the updated version of the course and lab with the new Tensorflow.org tutorials with Keras etc. Sorry about the 2 stars, apart of that I learned important things in the lab and course. I'll give a 5 stars with the updated version. Thanks.

por Sudhindra D

Nov 09, 2019

Data too huge to process within timeline of lab

por Tim K

Nov 27, 2019

super exciting topic but there are some issues with the labs. That's super frustrating

por Bo Y

Aug 27, 2017

Not updated, python 2.7

Too many small clips, should build a 4 modules * 10 videos *10 minutes each

GCP also changed, not find the right place to execute the code. Local docker encounter some issue, so I give up the code part. Really pity, that is what i am looking for

por Aleksei

Oct 10, 2019

There are many problems with the Datalab and mismatching between "mlengine" in the course and "ai-platforms" at GCP

por Marcelo G

Jun 22, 2018

Subtitles with lot of problems.

por Daniel I

Jan 17, 2018

It's ok as an introductory course, but videos are not aligned with labs, and I expected to extract deeper knowledge from it.

por Brett W

Nov 08, 2018

The labs are incredibly slow - I also think you need a better background in the technology being taught to understand what is going on. Again, a lot of the quiz q&a aren't covered by the material - also - trying to get support via the discussion forums is a fruitless exercise, my post was ignored - and the course is done.

por Henrique T

Sep 11, 2018

The content was good, but the labs are awful. It is already done, so you only have to play it. It isn't helpful and I don't think anyone can learn this way. The ideal is to be like the other labs, where you had to input the code yourself. This might be a very hard subject to keep in mind.

por Ciprian D

Feb 02, 2019

This course/specialization is seriously insufficient in order to pass the GCP certification. A lot of knowledge from the Architecture course would still be necessary. The disclaimer about work experience does not cover that.

por Leo Y

Jul 10, 2018

The most of the subtitles of this course are either out-sync or totally incorrect. Please fix it ASAP!!

por cheng y

Oct 09, 2017

the worst course in the Coursera