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返回到 End-to-End Machine Learning with TensorFlow on GCP

学生对 Google 云端平台 提供的 End-to-End Machine Learning with TensorFlow on GCP 的评价和反馈

4.6
883 个评分
137 个审阅

课程概述

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 <<< COMPLETION CHALLENGE Complete any GCP specialization from November 5 - November 30, 2019 for an opportunity to receive a GCP t-shirt (while supplies last). Check Discussion Forums for details....

热门审阅

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.

筛选依据:

101 - End-to-End Machine Learning with TensorFlow on GCP 的 125 个评论(共 138 个)

创建者 Aditya h

Sep 12, 2018

Good overview of end to end ML utilizing GCP starting from preparing the data set from Bigquery , utilizing data lab for building the model on a smaller dataset, Moving to Cloud ML engine to perform distributed training on a larger dataset, using Apache beam for pre-processing the data before serving and google app engine to finally serve the model

创建者 Jonathan S

Oct 13, 2018

It is an amazing demonstration of what Google Cloud can do in just a few lines of code, but a couple of the labs did not completely work for me, especially when it came to running jobs on Cloud ML. They were not essential, and the experience was still great.

创建者 Cristobal S

Oct 29, 2018

Great overview of the tools needed for deploying models for GCP. 4 stars are only because of lab technical issues.

创建者 Win S

Nov 21, 2018

Very hard to understand all the code, is there any prerequisite for this course? // It is seriously hard.

创建者 Hemant D K

Nov 24, 2018

Its good one.

创建者 Daeyong J

Jun 22, 2019

The contents are good but some materials have buggy code. (lab 4, lab6, lab7). Those labs cannot finish but I have to accept the concept what the teachers are saying

创建者 Putcha L N R

Jun 20, 2019

Pretty good start to the specialization, by reviewing the topics of the previous specialization! Looking forward to the rest of the specialization!

创建者 Saurabh R

Jun 30, 2019

Great Course with exposure to end to end deployment and Code Sample to learn Faster

创建者 Junhwan Y

Jun 29, 2019

This course is good to the beginner in first time. But, it has more complexity contents from middle. Also, every labs require quicklabs mission. it's very repeative. I recommend the simple task need to auto.

创建者 choisungwook

Jul 02, 2019

good

创建者 Gabrielwry

Jul 11, 2019

pretty good for intro to get a feeling of how the Machine Learning System is working as a product.

创建者 Jun W

May 27, 2019

Nice content. Would be nice if students are required to write more codes, not just running the written codes .

创建者 QZ

Jul 21, 2019

The course is well structured. However, Google moves really fast when creating new products hence there is some confusion when running the labs. That being said, it's amazing that qwiklabs is utilising essentially a live environment for practice.

创建者 Mohamad A

Aug 10, 2019

It is good course it contains all required to understand what you need to make and finalize and I learn all steps needed to make model ML app with google. However, there some notes sometimes I miss understand in labs there moving in code fast without explain maybe the labs for us to read later and at the end thanks to share with us your expertise and information

创建者 Prasenjit P

Sep 16, 2019

Good !!

创建者 Lanhsin L

Sep 29, 2019

It's good to quickly overview ML. But some syntax is not so friendly to understand if I didn't see the manual .

创建者 Mr. J

Sep 05, 2019

great survey of it. optional labs should be mandatory I think. Also it would be nice to have a end to end walk through in summation. another option to complete the mental model it to map notebook sections to the GCP infrastructure in a presentation.

I wonder about cloning the gcp repo locally to use it as a local template to further study. In other words I fire it up in my account later. or I access GCP via anaconda jupiter. Just wondering.

创建者 Manu G

Oct 04, 2019

Course covers the fundamentals of GCP with TF. Although the labs don't require much of a coding, and the ones which require have a poor structure because after each subtask say Task 1, you should be able to see if your code outputs the correct output, so for that they should have included some testcases. Also in the training part, quicklab has limit of 2 hrs, but training takes about 40-50 mins for a lower input size, and that lab requires to run training 3 times, so I was forced to just trim down the input size to fit all tasks within the lab time limit.

创建者 Ian Q T C

Jan 19, 2019

Exactly what it says. Labs are trivial and I felt like I didn't learn much other than how to use the interface for serving and taking a model from start to finish. The core concepts are useful both in GCP and if you decide to roll your own stack

创建者 David K

Mar 12, 2019

Good: Course structure = great, content is relevant and interesting

Bad: Labs do not always work (e.g. deprecated GCP modules incompatible with apache-beam), code for labs already contains answers... would be nice to have "lab" file and "answer" file to make learning more explicit, also, the white guy with the mustache should rerecord his videos.... the cadence is distracting and he does not go into as much depth as Lak

创建者 林佳佑

Nov 02, 2018

the course is helpful for any learner initial to touch GCP learning

创建者 Mark Y

Jun 22, 2019

nice

创建者 정은성

Jun 29, 2019

I am satisfied with GCP training except for some errors.

I think I need the latest update.

创建者 길경완

Jun 30, 2019

well