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学生对 Google 云端平台 提供的 Intro to TensorFlow 的评价和反馈

4.5
1,952 个评分
212 条评论

课程概述

We introduce low-level TensorFlow and work our way through the necessary concepts and APIs so as to be able to write distributed machine learning models. Given a TensorFlow model, we explain how to scale out the training of that model and offer high-performance predictions using Cloud Machine Learning Engine. Course Objectives: Create machine learning models in TensorFlow Use the TensorFlow libraries to solve numerical problems Troubleshoot and debug common TensorFlow code pitfalls Use tf.estimator to create, train, and evaluate an ML model Train, deploy, and productionalize ML models at scale with Cloud ML Engine...

热门审阅

DW

Oct 17, 2018

pretty good. some of the code in the last lab could be better explained. also please debug the cloud shell, as it does not always show the "web preview" button ;) otherwise, good job!

SS

Jun 06, 2018

Nice introduce, might be more on introduce the model structure, because I still need to read additional notes to locate how to train my deep learning model online.

筛选依据:

101 - Intro to TensorFlow 的 125 个评论(共 208 个)

创建者 Cesar R L S

Jan 18, 2020

Very good

创建者 Carlo B

Oct 03, 2019

Very nice

创建者 Víctor D L T

Jul 23, 2019

excelente

创建者 Nayanajith P

May 26, 2019

It's nice

创建者 borja v

Jun 17, 2019

Perfect!

创建者 Zhuqing X

May 04, 2019

Love it!

创建者 영신 박

Apr 27, 2019

Awesome!

创建者 Terry L

Apr 26, 2019

이 과정을 끝ㄴ

创建者 Bielushkin M

Nov 11, 2018

good job

创建者 Sujeethan V

Mar 26, 2019

Amazing

创建者 Aldi N S

Jan 24, 2020

Great

创建者 Ahmad T

Aug 26, 2019

Great

创建者 Loganathan S

Aug 02, 2019

Good!

创建者 江祖榮

Sep 19, 2019

Good

创建者 Fathima j

May 11, 2019

good

创建者 Dong H S

Apr 28, 2019

good

创建者 Atichat P

Jun 02, 2018

Good

创建者 Girish S K

Jul 22, 2019

The course was good introduction to tensor flow I learned lot of basics which otherwise I could not have learned from books or other online materials. The concepts are well explained. What I am not happy is about the Datascience labs. In places where internet is slow it is very difficult to do it. Instead of this in we are provided some alternate instructions to run them on a local machine that would have helped at least for some of the first few labs. I know that all of them cannot be run on local machine then the whole purpose of learning tensorflow on Google Cloud is defeated. The whole purpose is to learn how to run it on a cloud environment with scaling. I know that is not possible on a local machine. Another option would be to provide instructions to run the code with without notebook. I basically do not like notebooks , I Prefer command line to notebooks to execute and see results live. But overall I got a good intro about tensorflow - Thankyou very much.

创建者 Benny P

Dec 05, 2019

First of all we need to understand that TensorFlow is not just a Python toolkit. It's a complete tools from Python library, training management, monitoring, down to deployment to cloud or what have you. Therefore this course should be viewed as getting started introduction to ALL of that, not just the toolkit. And I think it's quite good. There are few glitches here and there when it comes to interacting with the GCP, but that's fine, you're learning something while fixing it. The disappointment comes from the forum though, as the staff's only response seem to be to shift the responsibility to Qwiklabs

创建者 Yaron K

Jul 14, 2018

An excellent introduction to TensorFlow, Including debugging tips, and how to scale up TensorFlow models and deploy them. So why only 4 stars ? because there is no audit option for this course and the videos can't be downloaded. Presumable the notebooks with sample code can be cloned from Github - but it seems the explanations will not be available unless you re-enroll. This policy is even more inexplicable considering that the course serves as a "presale" for the Google cloud platform.

创建者 David M B

Feb 26, 2019

Very useful but I had some problems with lab infrastructure. Options to create buckets wouldn't appear sometimes and I had to open and close google cloud console to make it work sometimes. Regarding the course it was great but there is a lot of boilerplate code and though the steps are simple and clear there is a lot to digest, I will need much more time master this TF/GCP workflow, but anyway this is a great start.

创建者 Sachin A

Jun 16, 2018

I think a lot of the lab-explanation given in the video following the qwiklab should be in the python notebook; make it a little more illustrative (e.g. architecture diagrams). Also, be a little more generous with the lab time - the last lab was too long (or perhaps change the code to select the faster ML option - standard/TPUs etc. to make the training go faster)

创建者 Zhenyu W

Jan 20, 2019

One of the lecturers should improve his English speaking. The course should add more contents, explanations, and exercises for the 3rd part of the course regarding how to scale TF models with CMLE, for example, some bash cmds or some code are confusing, unless this content will be covered more in the following courses.

创建者 Thibault D

Sep 10, 2019

I enjoyed this course a lot. If I could modify anything, I would adjust the content and pace of the third week. The videos are relatively simple to understand and well-explained while the final lab feels a lot harder with a lot of unknown command to execute.

创建者 Asmit M

Jul 30, 2019

hands on demonstrations were good. More in depth explanation can be done fro some of the codes including the part in which data fatching from the json file was explained, and the process to be followed in the gcp to make the model and deploy it.