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.
Excellent 'Introduction' to TensorFlow 2.0 (HINT: 'Introduction' does not mean 'Easy').\n\nEvan Jones is at his best giving rapid intuitive explanations of advanced topics in deep neural networks.
교육 기관: nicolas j•
/!\ 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•
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: CHRISTOPHER M•
This course needs to be revised for TensorFlow 2.0
교육 기관: Nithin•
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: Chen C•
This course(especially Week 3 ) is not for Tensorflow beginners at all. The lecturer in Week 3 uses various concepts that have not been introduced at all. I wonder if I have already known so many concepts, why on earth I need to take this course. In week 3, a lab is given without any examples demonstrated in the video.
교육 기관: Sudesh A•
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: Edrian S•
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: ujwal s•
Great discussion on TF infrastructure. Need to be updated to TF2.0
교육 기관: john f d•
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: Eddie G•
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: Juan M P•
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•
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: George•
labs were not properly working...
교육 기관: Ritayan G•
Goes from 0 to 100 really fast without any sort of teaching whatsoever. And within no time you are asked to write up an actual deployable ML model using core tensorflow. Which is just a tad difficult for beginners in Tensorflow.
교육 기관: Raghuram N•
Good introductory course on Tensorflow.
교육 기관: Aditya h•
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: Marc v W•
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•
This course is more focused on integration of other google services in TF rather then being an Intro to TF.
교육 기관: Richard K•
The course could have more programming components.
교육 기관: Ankoor B•
It is an easy course. The course could have been harder with graded exercises.
교육 기관: Thomas A•
Course skips over a lot of important aspects for an introduction course. Doesn't properly test the items they teach. The labs are basically read the answer and try to figure it out because half the time it's not discussed in the videos.
교육 기관: Brian R•
If you want videos rushing over 1 example of each high level element of a TF estimator and notebooks that people have put 0 effort into designing for actual learning and retention, this is the course for you.
교육 기관: Ehsan F•
nothing fancy or special or deep. just a superficial introduction.
교육 기관: Kevin•
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•
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