2 de jul. de 2021
Interesting material. There are quite a lot of typos and many code snippets are directly from the tfx manual pages however the instructions provided and logic of the course is clear.
13 de oct. de 2021
It is a very informative course. I learned a lot about data, metadata, schema and feature engineering, Also, Robert Crowe sir is a very good teacher.
por Enrique C•
4 de ene. de 2022
Good intro but it looks like in other courses from deeplearning.ai, while they teach you something, they also try to "sell" people a specific framework. In this case, they seem to be selling TFX, whose API seems to be in constant flux with no guarantee (maybe not effort at all) of backwards compatibilty. It is very likely that if you download a notebook and try it in your computer, unless you're using the same library versions, it would not work. Some quizes seem to be not in sync with the lesons content (questions are about the content off the next session). not acceptable for a platform like Coursera that has horrible customer support and that is ruthless with users that have issues with their payment method.
I still recall how they sold people the Trax library in the NLP specialization which seems to have replaced Trax with huggingface. I take what is useful from these courses but I distrust their agenda.
por Antonis S•
9 de mar. de 2022
+ New cool way of working with many possibilities
-Many new concepts and code with no clear connection to the "known" way of working.
-New code concepts not very clearly explained Urgent suggestions for improvement: Make the new concepts and code clear to the audience. Connect the examples to the previous way of ML
por Hui J•
4 de ene. de 2022
A lot of the concepts are not well-explained. I feel like my mind is constantly drifting away when watching the video, to me, this course is more like a workshop/ads for tensorflow rather than explaining the data lifecycle properly.
por Reto A W•
10 de nov. de 2021
I was not happy with the course. In the part 1 the lecturer showed a lot of real world example of developing big ML-systems. The lecturer for this course is more a library creator than a user of it. And therefore also it feels like an advertisement for tensorflow. Which is an odd combination for me. So it does not teach a lot of useful theory because it focuses on how tensorflow manages pipelines and not a lot about the concepts. But also the programming examples are very artificial examples taken from the tensorflow tutorials or documentation. What I liked in the first course was the practical view on a specific problem. The programming exercises I also did no like because I did not learn anything useful. I only "learned" to use tensorflow a bit. But the concepts implemented are so basic that they are not interesting at all. I am aware that this has to be like this if we are not expected to program for two day but I don't see the benefit for me of solving mandatory useless exercises. The result of this was: I was skipping through the videos in 2x and was solving the quizzes as fast as I could. Speaking of quizzes. There were quizzes asking questions never mentioned in the videos and once the quiz was posed before the video where the things were explained. Also the quizzes used unusual wording for concepts plus not clearly written questions. In the end there were some useful insights here and there but it was quite an effort for me to filter them out as my motivation was lacking after some time.
por Arturo M•
10 de may. de 2022
I'm quite dissapointed by this continuation of the otherwise excellent Andrew Ng specialization.
I was expecting a course on frameworks and best practices for managing data in MLOps environments. Instead, this course is basically a commercial of Tensor Flow Extended, a MLOps framework by Google. Other tools often used in commercial applications (like cloud ML platforms) are not even mentioned.
It's true that the course does provide some tips, but they are often too general to be of practical use, specially for people with some experience in the field (e.g. "you need to validate your inputs").
I hope the next courses in the specialization are better.
por Nithiwat S•
23 de jun. de 2022
The course is poorly prepared and presented. The instructor basically talks through slides with no concrete technical content, simply babling from one bullet point to another, from one slide to the next, unorganized. Lectures were horrible -- broad, technical content barely scratches the surface, uninteresting way to deliver and speak. This is a practical course. The intructor should have structured the lecture around a practical implementation through a real-life example. It's not there at all. Very difficult to continue listening and it's very frustrating. Lab and Assignments in Jupyter Notebook are good. Overall, a huge disappointment considering the first course in the Specialization taught by Andrew Ng was so good.
por Shreyas R C•
21 de jul. de 2021
Best course for the professionals looking to upgrade there ML skills at production level! Thanks to the brilliant and wonderful course instructor.
por Youngjeon L•
11 de sep. de 2021
Nice, Awesome MLOps Pipeline with TFX! I recommend this course anyone who want to build ml pipeline! Good Luck! :)
por Nam H T•
16 de ene. de 2022
Great course with useful exercises to get learner familiar with ML Data pipeline using TensorFlow Extended!
por Fernandes M R•
19 de jun. de 2021
Its good, I think was a little difficult because TensorFlow, but it was very explicative.
por Luis S S•
10 de sep. de 2021
Excellent course. Theory and practice well combined, to fit diverse curiositiy levels.
por Han B•
15 de ene. de 2022
instruction on debugging jupyter and submission issue is important for learners
por Tom v D•
21 de ago. de 2021
This was my first course with Robert, which was a very pleasant experience.
por Zanuar E R•
24 de dic. de 2021
It is really good course, the detail explanation of Data LifeCycle in TFX!
por Walt H•
8 de sep. de 2021
You can immediately apply everything you learn in this course!
por Hieu D T•
15 de ago. de 2021
Some questions are difficult. Lots of new terms. Great course!
por Pierre-Alexandre P•
9 de jul. de 2021
Very good training about data lifecycle for ML projects
por Meng C•
13 de ene. de 2022
Great overview and labs for cutting-edge TFX platform.
por Fady S•
25 de jul. de 2022
Excellent material and comprehensive assignments
por David B M•
26 de dic. de 2021
Podría ser cool el modo dark en los laboratorios
por Barata O•
5 de ago. de 2022
Many Hands-on to help understand the materials.
por Chandan k•
22 de jun. de 2021
A good course indeed to pursue my dream job !
por Thành H Đ T•
8 de ago. de 2021
it's very nice. thank you so much
por Shannen L•
29 de jul. de 2021
very helpful for ml engineers
por Shan-Jyun W•
15 de ene. de 2022
Great course! Very Useful!