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.
por 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
por 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,..
por 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.
por 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 ?
por 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.
por 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.
por 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.
por 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
por 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!
por 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.
por 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
por 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.
por 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 .
por Jun W•
May 27, 2019
Nice content. Would be nice if students are required to write more codes, not just running the written codes .
por Win S•
Nov 21, 2018
Very hard to understand all the code, is there any prerequisite for this course? // It is seriously hard.
Jul 11, 2019
pretty good for intro to get a feeling of how the Machine Learning System is working as a product.
por Saurabh R•
Jun 30, 2019
Great Course with exposure to end to end deployment and Code Sample to learn Faster
por Michał M•
Jan 16, 2020
More explanation and digging deeper into code would be welcomed
por Hemant D K•
Nov 24, 2018
Its good one.
por Luis E O•
Apr 04, 2019
por Prasenjit P•
Sep 16, 2019
Jul 02, 2019
por 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