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.
автор: Atichat P•
Oct 03, 2018
автор: 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.
автор: 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.
автор: Samarth G•
Apr 13, 2020
Good course. It gives a nice overview of how to build a ML model on GCP and deploy it to be used as a REST API. The labs could be improved. I found the lectures to be extremely helpful. The teachers do a great job at explaining the concepts. The labs give a hands on to what we study in the lectures. However, the labs could be improved. Some of the labs have issues that need to be fixed.
автор: Rohan S•
Feb 24, 2019
This course is more suitable for learners who have some prior familiarity with machine learning. For people who are unfamiliar with the Google Cloud Platform, this course walks you through all the steps required to build a simple model on Google Cloud Platform. Overall, the course was good, but I would recommend previous experience with machine learning to avoid stalling.
автор: 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
автор: 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
автор: Lloyd P•
Jan 01, 2019
The qwiklabs interface to GCP is a little cumbersome. The need to start and stop sessions with each lesson wastes some time. I would prefer if the course came with a GCP credit and we were able to use our own accounts and still have a way to keep track of progress,..
автор: 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.
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.
автор: vincent p•
Feb 06, 2019
Needs more explanations about the performance.
I do not understand why processing is so slow.
it is dozens of minutes or even more than 1 hour to process a few gigabytes.
Datalab takes more than 5 minutes to start, why ?
автор: Mauro B•
Sep 19, 2018
Interesting hands-on course. You can grasp the full workflow from exploring a dataset, select/validate and transform inputs, define the model, train and validate it in a small scale and on Google Cloud Engine.
автор: 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.
автор: arnaud k•
Jan 09, 2019
Overall this is a very well structured and well delivered course i learned a lot from it.
But I couldn't reproduce some of the examples on local machine so 4 stars for now.
автор: Shray B•
Apr 14, 2020
Good walkthrough and VERY valuable information. Only problem is that some of the notebooks didn't work when I ran them and they were different from the video tutorials.
автор: 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
автор: 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!
автор: GOUTHAM R K•
May 08, 2020
its good than i thought , you will learn clearly what you need to learn . especially tensor flow and ML in particular estimating the baby weight.
автор: Muhammad S S•
Jan 23, 2020
The course is very well managed and very well delivered. The labs gave an opportunity to learn the course from implementation point of view.
автор: Michael H•
Feb 08, 2020
Notebooks for labs would not open sometimes. They would just spin and I wouldnt be able to open a new instances (using chrome incognito).
автор: Jeffrey G•
Dec 22, 2019
Hits the sweet spot of not trying to teach you model development or TF but still shows how to integrate with the GCP mindset.
автор: Luis B•
Nov 29, 2019
This is a very good introduction, I regret not being able to do optional lab 7 (no qwiklabs) an seing the app live
автор: 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.
автор: 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 .
автор: Jun W•
May 27, 2019
Nice content. Would be nice if students are required to write more codes, not just running the written codes .