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TensorFlow 소개(으)로 돌아가기

Google 클라우드의 TensorFlow 소개 학습자 리뷰 및 피드백

4.4
별점
2,418개의 평가
291개의 리뷰

강좌 소개

This course is focused on using the flexibility and “ease of use” of TensorFlow 2.x and Keras to build, train, and deploy machine learning models. You will learn about the TensorFlow 2.x API hierarchy and will get to know the main components of TensorFlow through hands-on exercises. We will introduce you to working with datasets and feature columns. You will learn how to design and build a TensorFlow 2.x input data pipeline. You will get hands-on practice loading csv data, numPy arrays, text data, and images using tf.Data.Dataset. You will also get hands-on practice creating numeric, categorical, bucketized, and hashed feature columns. We will introduce you to the Keras Sequential API and the Keras Functional API to show you how to create deep learning models. We’ll talk about activation functions, loss, and optimization. Our Jupyter Notebooks hands-on labs offer you the opportunity to build basic linear regression, basic logistic regression, and advanced logistic regression machine learning models. You will learn how to train, deploy, and productionalize machine learning models at scale with Cloud AI Platform....

최상위 리뷰

VC

May 18, 2020

I feel this course very valuable because it taught how to create an automated service in cloud with very huge data and working with distributed systems in production environment with minimal time.

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!

필터링 기준:

TensorFlow 소개의 287개 리뷰 중 151~175

교육 기관: Simon Z

Jun 05, 2020

At a couple of important points in the course (e.g. where it is about launching TensorBoard or even more important where it is about deploying the model with ML Engine) the code in the Lab differs substantially from what is shown in the discussion of the lab. This is a little irritating. That aside, I have learned a bunch of new techniques and processes to improve my coding and especially: code more quickly and scalable. Thanks for some really good lessons.

교육 기관: 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.

교육 기관: 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)

교육 기관: 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.

교육 기관: James S

Apr 20, 2020

I could not get my final lab project to work. I have sent the issue to Qwiklabs - I got the following error message:

ls: cannot access '/home/jupyter/training-data-analyst/courses/machine_learning/deepdive/03_tensorflow/labs/taxi_trained/export/exporter/': No such file or directory

교육 기관: 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.

교육 기관: 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.

교육 기관: Carlos V

Jun 24, 2018

Excellent course in the capabilities of tensorflow, the course material and data-lab examples are super useful and provide a good overview of how to implement tensorflow models locally and in the cloud with high-quality practices.

교육 기관: Benjamin B

Sep 26, 2018

Challenge problems at the end of each assignment are really good, however, there should be videos showing how the instructors would solve them, I would be fine watching 30 min videos describing the solutions. Nice course!

교육 기관: Vijay K

Mar 30, 2020

Intro to TF should have packed with more fundamental concepts around TF alongside existing topics covered. Moreover, some of the code needs either further explanation or references to understand what a given code is for.

교육 기관: Bartosz C

Apr 23, 2020

There were some technical problems. Some of the exercises could be described in more detail with TODOs.

Nevertheless I very much enjoyed the course. Quite an amount of material. Challenging tasks. You can learn a lot.

교육 기관: GAURAV B

Feb 13, 2020

Was expecting a bit more around tensorflow basic concepts. Coverage was too much from basic to production level deployment. Was expecting a bit more hands-on on tensorflow basics and details around deployment.

교육 기관: Loucas L

Aug 31, 2019

The tools and methods presented were great. The instructors were also fantastic.

However the coding exercises were lacking in guidance even though the complete solution is given in the video.

교육 기관: Tom W

Mar 31, 2020

This needs some updating - looks like the Tensorboard is no longer accessed in the same way as it was when this course was produced.

Otherwise great! Good challenges! :/

교육 기관: andy g

Jun 27, 2020

The first week was the best, as it described some of what's going on under the hood. I would have liked much more on these topics and less on specific cloud products

교육 기관: Yuvaraj G

Apr 05, 2019

The procedure to connect to the cloud datalab was time consuming to do it every time.

Suggestion : More topics in Core Tensorflow could be added. I enjoyed the course!

교육 기관: Quoc B D

Jul 05, 2018

Good general TensorFlow introduction. The course focuses on the highest level tf.Estimator whereas there are maybe something interesting low level they don't present.

교육 기관: Misho K

Mar 09, 2020

The course covers quite a few concepts -- TF basics, TF estimator, Google Cloud ML. It would be easier if the material is split into TF and Google Cloud lessons.

교육 기관: Tyler B

Oct 07, 2018

Great course as an introduction to TF, however, the labs are not as in depth as I'd have liked. Nonetheless, the course is well executed by the presenters.

교육 기관: Stefan K

May 11, 2020

A good understanding of bash cmds and a well-digested understanding of the course material is required to perform the labs. Quite challenging.

교육 기관: Dimitry I

Nov 06, 2019

Good course. Familiarity with gcloud command should be a prereq. Thank you to Coursera and the Google team for putting it together.

교육 기관: Anupam S

Dec 01, 2019

Week 1 and 2 were great and quite detailed. Week 3 was too condensed. Overall better than Course 2 of the specialization series.

교육 기관: RLee

Jul 22, 2018

Not very elaborative in Week 3. Correct me if I am wrong, the 3rd week lab feeds in still in-memory data from a local file.

교육 기관: Janith G

Jul 21, 2020

Good course to understand basics of Tensorflow. Its better to update the course content with Tensorflow 2.x. Thank You.

교육 기관: Alexander Z

Dec 03, 2018

Good course! Sometimes I was not 100% sure what I was supposed to do. But the solution videos made it clear afterwards.