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End-to-End Machine Learning with TensorFlow on GCP(으)로 돌아가기

Google 클라우드의 End-to-End Machine Learning with TensorFlow on GCP 학습자 리뷰 및 피드백

4.5
별점
1,245개의 평가
197개의 리뷰

강좌 소개

In the first course of this specialization, we will recap what was covered in the Machine Learning with TensorFlow on Google Cloud Platform Specialization (https://www.coursera.org/specializations/machine-learning-tensorflow-gcp). One of the best ways to review something is to work with the concepts and technologies that you have learned. So, this course is set up as a workshop and in this workshop, you will do End-to-End Machine Learning with TensorFlow on Google Cloud Platform Prerequisites: Basic SQL, familiarity with Python and TensorFlow >>> 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 <<<...

최상위 리뷰

GP

Nov 18, 2019

awesome learning experience fro the teacher from google. thanks to coursera and google for providing me such a good lesson which will be beneficial for my upcoming future and research work

SA

Mar 03, 2019

Definitely adds a unique perspective on thinking about machine learning systems at scale. This course is suitable for Data Scientists, Data Engineers and Machine Learning Engineers.

필터링 기준:

End-to-End Machine Learning with TensorFlow on GCP의 197개 리뷰 중 1~25

교육 기관: Kevin M

Dec 06, 2018

Not enough hands-on labs. Mostly just videos and running existing python code. Had to write only a tiny amount of code. I won't remember any of the code, I'll just remember ctrl-enter on all of the pre-written python.... could definitely use some improvement.

교육 기관: Panit A

Apr 27, 2019

Would be nicer if students can use the google cloud with less restrictions. I got blocked multiple times from trying the codes in the videos..

Overall, the materials are great and very interesting!

교육 기관: Hammad A

Apr 12, 2020

Quite outdated this course needs to be updated or removed.

교육 기관: Carlos V

Oct 07, 2018

One of my favourites Courses from Google, it provides an excellent overview of the End to End Machine LEarning process, and how to use GCP to speed up your workflow, highly recommended to anyone looking to expand their understanding of Real World application of ML

교육 기관: Harsh S

Jun 09, 2019

Objective of course is great. But, a lot can be improved in terms of clarity on how to execute this course. It is not clearly mentioned whether we need to just execute provided notebooks or write code from scratch. Moreover, how to copy these notebooks from Google cloud repo on github is not mentioned anywhere.

교육 기관: Soh Y L

Apr 07, 2020

This course was created in end of 2019. It will be much better to update the lab materials to Tensorflow 2.0 and use Keras abstraction. The goal is to learn how to deploy without going into too much details. Some of the code doesn't work in 2.0 anymore.

교육 기관: Brandon T

Dec 12, 2019

I appreciate the content being on github but the course had many technical difficulties on GCP. Much of the content in videos was in python2.

교육 기관: Maxim

Jul 05, 2019

This specialization consists of 5 courses:

Course1: End-to-End Machine Learning with TensorFlow on GCP

Course2: Production Machine Learning Systems

Course3: Image Understanding with TensorFlow on GCP

Course4: Sequence Models for Time Series and Natural Language Processing

Course5: Recommendation Systems with TensorFlow on GCP

In specialization's FAQ say nothing about "audit" option. Do You know what is it ? "Audit" means that You can use course video material even after You subscriptions ended.

By fact, only "Course 1" has such ability. Before pay for specialization, carefully check FAQ for EACH separated course in specialization:

courses 2-5 has special point:

"Why can’t I audit this course?

This course is one of a few offered on Coursera that are currently available only to learners who have paid or received financial aid, when available.

"

"Who have paid" means that after You subscriptions ended, you lost access to video materials in this courses.

p.s.

1 star only for "Audit", content and lecturers are rated higher - at least 4 stars

교육 기관: charles l

Dec 13, 2019

Spent more time with Google tech support trouble shooting why their courses didn't work, than I did on machine learning...

교육 기관: Ahmed I K

Apr 04, 2020

Too many errors generated when running the code cells provided in the notebooks

교육 기관: Satwik R K

Apr 15, 2020

Not worth of investing Time on it.

교육 기관: Pierre L M

Sep 30, 2019

Good course overall, maybe the labs are too short or too easy, maybe it would be better to have a link to a doc with some related tasks.

Two labs were missing, one I could see while looking around in the notebooks, but the last one I didn't, i would have appreciated since I don't know flask yet

교육 기관: Sergio B S

Nov 04, 2018

This first course of the specialization allows to jump from the ML model that one can play in its own computer, to the model that you can scale to become business operative.

It is not only about build the model, it is about publish the model to make it avalible to your customers or consumers!

교육 기관: Wang Y

Nov 11, 2018

One of the best course in the series! A comprehensive tutorial that walk your through the whole end-to-end process of machine learning. Hope there is more similar courses like these where we can get our hands dirty with practical end-to-end machine learning case studies!

교육 기관: Manthan R

May 31, 2020

I genuinely thank the course co ordinatos for such an amazing experience. The amount of information i was able to adsorb was just fabulous. Once again, a worthy course to go for if you're keen in learning machine learning end to end process. Thanks alot!

교육 기관: Javed S

Nov 28, 2018

This course contains many helpful hands-on labs. The course instructors are very knowledgeable. I would recommend this course to anyone who is interested in learning about production machine learning pipeline using TensorFlow.

교육 기관: Satyabrata P

Jun 18, 2019

This course is very help full for the beginners where one can learn the ML model to Create , Train , Evaluate & Deploy , very live examples and hands on lab .

My sincere thanks to the training instructors for their efforts.

교육 기관: Roman V

Feb 09, 2020

Very practical course. I recommend it to people who already has good ML background and know how ML algorithms work. It is a great practical introduction on how to quickly build and deploy your model in GCP

교육 기관: Gunjan P

Nov 18, 2019

awesome learning experience fro the teacher from google. thanks to coursera and google for providing me such a good lesson which will be beneficial for my upcoming future and research work

교육 기관: Serhan A

Mar 03, 2019

Definitely adds a unique perspective on thinking about machine learning systems at scale. This course is suitable for Data Scientists, Data Engineers and Machine Learning Engineers.

교육 기관: Kevin G T

Oct 07, 2018

A very helpful course, we were able to practically apply all the knowledge we received from the First Specialization. I feel much more confident to do ML after this course!

교육 기관: Rahulkumar S

Mar 28, 2020

The course content is rich and easy to understand. The instructors are also awesome and the quick labs are very helpful to understand the concepts in the practical world.

교육 기관: SAJJA R K

Oct 15, 2018

Excellent opportunity to learn ML for real world applications. Every one will get the benefit after completion of the course. Thanks for providing such a nice course.

교육 기관: Ilias P

Nov 26, 2018

The course is really Great! It takes you so smoothly from the beggining to the end. I didn't have to watch something for a second time. Everything is well explained!

교육 기관: Harold L M M

Nov 04, 2018

This is a great start for advanced ml on gcp. The course labs require that you code the TODO parts, and therefore helps you gain the required coding knowledge.