Oct 17, 2018
pretty good. some of the code in the last lab could be better explained. also please debug the cloud shell, as it does not always show the "web preview" button ;) otherwise, good job!
Jun 06, 2018
Nice introduce, might be more on introduce the model structure, because I still need to read additional notes to locate how to train my deep learning model online.
교육 기관: nicolas j•
Dec 08, 2018
/!\ THIS COURSE IS A FRAUD /!\
this course is a way more about google cloud than tensorflow:
-You'll never learn how to install and setup tensorflow on your own infrastructure. Count how many time the logo of google cloud vs tensorflow appears. Another fact? they propose to win a google cloud tshirt on the forum... but you'll learn how to use google cloud...
-Tutors tell to don't use the forum on coursera, but the google tickets system... but as long as I pay on coursera, I expect to have a serious following from the tutors on the coursera forum, isn't it legit ?
-Of course they don't forget to send you email about google cloud products...
-You only have to pass quiz, no need to do the exercises, just log to them then your good to pass... is that serious ? what does worth my certificate ?
-I'm definitely not happy of this one, this will down my confidence in coursera...
btw I will send this message to coursera either in the way to get some explanation how this could be possible... I mean we are talking about google doing a fraud!
교육 기관: MIchael•
Jan 23, 2019
even though the instructors present in a great way, especially the labs seem to be quite confusing and the videos couldn't prepare me so well for what expects me in the lab
교육 기관: Nithin S•
Jan 10, 2019
While it is a fairly basic and informative course, I could was left disappointed with a few things
I found the lab infrastructure hard to setup and of limited use.
The lab exercise were trivial and not up to mark
The lab was not graded or no scope for us to run them independently on our cluster on our own cloud.
I was slightly irritated with trainers trying to promote google product instead of focusing on technical training.
Google BigQuery was an unnecessary addition and distracting till you realize you don't need it for this training.
교육 기관: Sudesh A•
Jul 14, 2018
The introduction to TensorFlow was good. Lab needs improvement; it would be helpful to have code templates that needs to be filled in by us to get credit for the lab, instead of just executing the code. Content in Estimator API module needs a bit more depth/explanation in my opinion.
교육 기관: Juan M P•
Jan 31, 2019
Although the videos and content in general is OK, the environment and setup of Google DataLab for each lab is really disgusting – takes about 10 minutes to start with the proper exercise.
I understand that Google wants us to use their products, but the main purpose of this course (learning TensorFlow) is cluttered with this environment.
교육 기관: Miika M•
Nov 21, 2018
Don't think I'll remember much of what I've seen two weeks from now. Most of the time in the course was spent on spinning up the google cloud stuff. All the labs are done for you so no need to use your own brain. I'm very disappointed.
교육 기관: CHRISTOPHER M•
Apr 10, 2019
This course needs to be revised for TensorFlow 2.0
교육 기관: George•
Aug 06, 2018
labs were not properly working...
교육 기관: john f d•
Jul 18, 2018
Labs vms are to slow. Speaker is difficult to understand. Mic varies and speech pattern is not clear. The presentations need some graphics rather than a guy talking. Sketch out the ideas on a white board rather than talking 5 minutes to a single slide.
교육 기관: Raghuram N•
Apr 29, 2019
Good introductory course on Tensorflow.
교육 기관: Aditya h•
Aug 11, 2018
Pretty helpful in getting to know the various levels of abstractions of tensorflow API and avoiding various pitfalls while building the Tensorflow model
교육 기관: Ujwal S•
Nov 28, 2019
Great discussion on TF infrastructure. Need to be updated to TF2.0
교육 기관: Marc M v W•
Jan 21, 2019
Sadly disappointing. I was hoping for a more detailed presentation of TensorFlow and its capacities. But no words about the Keras level, TensorHub, and other TensorFlow really useful parts. Instead, we have a gentle "hello world" type of introduction to TensorFlow low level and estimation layers, and how to deploy an application to Google Cloud. Now it's not bad, just disappointing.
교육 기관: Muhammad A R•
Sep 29, 2018
This course is more focused on integration of other google services in TF rather then being an Intro to TF.
교육 기관: Richard K•
Jan 26, 2019
The course could have more programming components.
교육 기관: Eddie G•
Jan 16, 2019
This course is not for those starting out with Machine Learning; its language is very technical and not learner-friendly. Furthermore, for the labs, a new log in is generated for each lab so that you need to setup the virtual machine new each time, which takes forever. Furthermore, the labs are not structured well as they don't accurately reflect what was taught in the same section.
교육 기관: Ankoor B•
May 29, 2018
It is an easy course. The course could have been harder with graded exercises.
교육 기관: Ehsan F•
Nov 15, 2018
nothing fancy or special or deep. just a superficial introduction.
교육 기관: Edrian S•
Aug 08, 2019
Older reviews mention that Datalab takes a really long time to spin up, and that the code is pre-written for you so that you don't really "learn". Not sure when things changed (although there is a tag that says material changed around the 1st of July 2019), but the labs no longer use Datalab. They use Jupyter Lab accessed via the AI Platform on GCP. It still takes a couple of minutes for Jupyter Lab to start up, but it's way faster than Datalab. They've also included two notebooks. One doesn't have much, if any, code written out asking you to try your hand at writing it. The other is the solution code. Anyway, wanted to make sure that update was reflected in the most current reviews. I completed the course on 8/6/2019.
교육 기관: Kevin•
Jun 05, 2018
Great example code to help you gain an understanding of cloud ML Engine prior to understand the deeper insights needed to make better machine learning model. Good Tensorflow overview with the estimators API along TensorBoard. It is a good end to end touch of the "ugly side" of data science people often glaze over. It's nice to see code that shows you how to scale a model because all too often online courses just teach you basic ML and nobody teaches you what to do when you run out of room on your individual computer. I would say the concepts are definitely intermediate and a prior understanding of basic ML like training, testing, predicting is needed in order the other topics of the course.
교육 기관: Mark B•
Nov 25, 2018
the vid on why cloud ML was great: e.g. taking things to a new level by offering distributed training to users
the debrief of the last lab was key.
some pointers re the challenge exercises would be nice.
Great job introducing users to tensor flow, the estimators and how to train and deploy in the cloud.
What was I looking at in the ML cloud log (last lab)?
Why was there a deadline for the assignments? I thought this was self paced learning. I like the material a lot yet my day job workload varies so having deadlines on labs that I would want to understand in more depth is sometimes not ideal. In any case. Great material . Thank you
교육 기관: Anupam K•
Apr 21, 2019
It is really a divine knowledge, If you are really a new to in the area of data science and especially to Tensor flow, With in a few weeks, I learnt so much and got a humongous confidence in building a model, Still long way to to go, But this course is really worth. Thanks Google Team and Coursera for putting things together .
교육 기관: Patrick M A•
Aug 04, 2018
It is a great course that does not go to deep into Tensorflow, but shows exactly with what purpose it was designed and how you can use it depending on your needs. There is also very nice example code that helps you start your own projects from a very nice and clean structure. So far, the best intro to Tensorflow I have seen!
교육 기관: Sinan G•
Aug 21, 2018
Amazing beginning of modelling to actual production, and a unique work flow that is relatively easy handle. Only thing I missed from the course was a more information, examples and explanation of how to actually produce and build the task.py file.
교육 기관: Jafed E•
Jul 06, 2019
I enjoy the lectures. The professor has a good speaking and teaching style which keeps me interested. Lots of concrete math examples which make it easier to understand. Very good slides which are well formulated and easy to understand