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
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.
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.
Jul 02, 2019
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 .
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
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
Nov 02, 2018
the course is helpful for any learner initial to touch GCP learning
创建者 Mark Y•
Jun 22, 2019
Jun 29, 2019
I am satisfied with GCP training except for some errors.
I think I need the latest update.
Jun 30, 2019