14 nov. 2020
Excellent 'Introduction' to TensorFlow 2.0 (HINT: 'Introduction' does not mean 'Easy').
Evan Jones is at his best giving rapid intuitive explanations of advanced topics in deep neural networks.
17 mai 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.
par Fathima j•
11 mai 2019
par Dong H S•
28 avr. 2019
par Atichat P•
2 juin 2018
par Cheikh T B•
27 avr. 2022
par Girish S K•
22 juil. 2019
The course was good introduction to tensor flow I learned lot of basics which otherwise I could not have learned from books or other online materials. The concepts are well explained. What I am not happy is about the Datascience labs. In places where internet is slow it is very difficult to do it. Instead of this in we are provided some alternate instructions to run them on a local machine that would have helped at least for some of the first few labs. I know that all of them cannot be run on local machine then the whole purpose of learning tensorflow on Google Cloud is defeated. The whole purpose is to learn how to run it on a cloud environment with scaling. I know that is not possible on a local machine. Another option would be to provide instructions to run the code with without notebook. I basically do not like notebooks , I Prefer command line to notebooks to execute and see results live. But overall I got a good intro about tensorflow - Thankyou very much.
par Benny P•
4 déc. 2019
First of all we need to understand that TensorFlow is not just a Python toolkit. It's a complete tools from Python library, training management, monitoring, down to deployment to cloud or what have you. Therefore this course should be viewed as getting started introduction to ALL of that, not just the toolkit. And I think it's quite good. There are few glitches here and there when it comes to interacting with the GCP, but that's fine, you're learning something while fixing it. The disappointment comes from the forum though, as the staff's only response seem to be to shift the responsibility to Qwiklabs
par Yaron K•
14 juil. 2018
An excellent introduction to TensorFlow, Including debugging tips, and how to scale up TensorFlow models and deploy them. So why only 4 stars ? because there is no audit option for this course and the videos can't be downloaded. Presumable the notebooks with sample code can be cloned from Github - but it seems the explanations will not be available unless you re-enroll. This policy is even more inexplicable considering that the course serves as a "presale" for the Google cloud platform.
par Simon Z•
5 juin 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.
par David M B•
26 févr. 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.
par Sachin A•
16 juin 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)
par Zhenyu W•
20 janv. 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.
par James S•
20 avr. 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
par Thibault D•
10 sept. 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.
par Asmit M•
30 juil. 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.
par Raj P•
14 avr. 2021
it was really excellent course to take, some of the complexities in the videos could have been easily explainable and vocabulary could have been easy for every age group for understanding,
otherwise it was amazing experience learning
par Carlos V•
24 juin 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.
par Ben B•
26 sept. 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!
par Ravi V K•
30 mars 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.
par Bartosz C•
23 avr. 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.
par Gaurav B•
13 févr. 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.
par Loucas L•
31 août 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.
par Tom W•
30 mars 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! :/
par andy g•
26 juin 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
par Yuvaraj G•
5 avr. 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!
par Quoc B D•
4 juil. 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.