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Отзывы учащихся о курсе Data Pipelines with TensorFlow Data Services от партнера deeplearning.ai

3.9
звезд
Оценки: 61
Рецензии: 19

О курсе

Bringing a machine learning model into the real world involves a lot more than just modeling. This Specialization will teach you how to navigate various deployment scenarios and use data more effectively to train your model. In this third course, you’ll use a suite of tools in TensorFlow to more effectively leverage data and train your model. You’ll learn how to leverage built-in datasets with just a few lines of code, use APIs to control how you split your data, and process all types of unstructured data. This Specialization builds upon our TensorFlow in Practice Specialization. If you are new to TensorFlow, we recommend that you take the TensorFlow in Practice Specialization first. To develop a deeper, foundational understanding of how neural networks work, we recommend that you take the Deep Learning Specialization....

Лучшие рецензии

GL

Mar 03, 2020

Laurence cares deeply about the students. Not only about what they learn, but that they actually enjoy and learn it. What a fantastic teacher.

NB

Mar 30, 2020

This seemed very helpful and hands on. I can't wait to try this on my own.

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1–21 из 21 отзывов о курсе Data Pipelines with TensorFlow Data Services

автор: Danilo C

Jan 31, 2020

I'm sorry but, it does not seem realistic pipelines, it clearly show the capability of tensorflow, but real world data pipeline on my point of view is completely different from that. I was expecting something like how to handle large amounts of data coming into the cloud, or onpremise cluster, and get it into a retraining pipeline, improving the models... but was completely different... If you are expecting something like, How to retrain a large model with large amounts of new data, realtime... that is not the course for you.

I love Andrew and Lawrence, but this last specialization is not at the same level from the other 3 from Deeplearning.ai, you guys should consider rethinking it using more Cloud deployment strategies with Tensorflow, like delivering APIs that requests model inference, and retrain automatically, using Google Cloud, Sagemaker, Azure whatever..., integrate it into a MLOps/DevOps model, and delivery at scale, at edge, that is the real world of deployment in my view...

автор: Andrei D

Feb 03, 2020

Excellent course both for Data Scientists and Machine Learning Engineers!

автор: Thomas A

Feb 05, 2020

The last exercise does not seem complete. There is too less help about solving the excercise - moderators do not help.

автор: Soren J

Jan 28, 2020

Some issues with notebooks. This is still in beta. Absolutely no help with the technical setup (notebooks and the Tensorflow datasets). Needs to be debug a couple of times..

автор: Evgeny K

Feb 14, 2020

Unfortunately this course is extremely weak. Tons of poorly explained code and nothing else

автор: Gant L

Mar 03, 2020

Laurence cares deeply about the students. Not only about what they learn, but that they actually enjoy and learn it. What a fantastic teacher.

автор: Ben D

Feb 21, 2020

Last week is a total disaster

автор: Michael

Jan 31, 2020

The course has a lot of practical experience and content. The reference material available, including the support is very limited. Which makes it hard to debug the code, you would literally spend days. I struggled on my on with no help whatsoever from the mentors in week 3. At least in week 4, there was some help. The balance between the quiz questions, which does not contribute in any way to the overall passing, and the practical is totally off. Maybe if we could get notes, to help us. Maybe just touch ups, but overall, Mr Laurence Moroney you are a great trainer. Looking forward to course 4.

автор: Liang-Chun C

Feb 11, 2020

It's a more advanced topic related to creating datasets which fit into TensorFlow data pipeline. However, lectures contain too much information per slide without highlight what the instructor was talking. A little bit hard to follow. Overall, This course include useful information and require additional time to organize all materials again. Thanks for making such an incredible course.

автор: Nicholas B

Mar 30, 2020

This seemed very helpful and hands on. I can't wait to try this on my own.

автор: Qi D

Feb 11, 2020

good,but the last exercise is a bit tricky

автор: Sayak P

Jan 27, 2020

Very practical!

автор: Cees R

Mar 24, 2020

I liked the topic and instruction of this course. I had bumped onto the notion of datasets earlier, was impatient as I needed to just resolve an issue, and skipped it. Next time I know what they are about and will be able - and happy - to use (including build) them.

Slight minus: presentation in the video often contained some bullets that I couldn't connect to the speech, that is, I had to choose: read or listen.

Bummer: the last week's exercise effectively required to copy-paste from a notebook that was scrolled through in the video. That is silly enough in itself. What is more, for certain errors in the created code in the notebook, the grader gave a standard notification that was not helpful in resolving the identifying what coding error had been made. As the discussion showed, a good number of people - me including - had been struggling with this to the level of feeling helpless to resolve it.

Still four stars for instructional value of the whole course, but I hope for the sake of future students that the above mentioned exercise will be replaced by a better one.

автор: Ковенко В А

Mar 29, 2020

Basically, i liked the course as I got lots of new knowledge about data pipelining using tensorflow. However, the one downside of the course is the last week's assignment, which is just awful.

автор: Marvin J C I

Apr 04, 2020

This course is quite essential, yet it is prepared too quickly? I had a hard time on Week 3 and Week 4 because the exercises are hard to grasp.

автор: András G

Feb 17, 2020

Dataset creation task was more complex for me then all previous before.

автор: Jinxiang R

Mar 01, 2020

week 2 and week 4 is quite hard to follow

автор: Pavel K

Mar 11, 2020

First three weeks were pretty interesting, especially pipelines and performance. However the examples and tasks were a little bit non-realistic. But Week 4 exercise was terrible. It is almost impossible to complete it using just grader's output. Running its copy in a separate colab's notebook is a must to be able to track errors, a lot of which are basically typos in names. The task description should have mentioned this much more explicitelly.

автор: Fabrice L

Mar 20, 2020

That makes me sad to give such a bad rating, because I'm a big fan of Andrew Ng and DeepLearning.ai courses, but this one is really not at standart.

The lectures are confusing, we don't understand what's the goal of all that until week3.

The assignments can be a pain to pass, not because your code is wrong, but because you added a newline or modify a bit the cell.

And overall the topic is not very interesting, in an industry setting not useful.

автор: Abelardo F B

Apr 04, 2020

Every nice part of this course is obscured by the shamely developed exercise in week 4. It's a GIGANTIC pain is the ass, as it was badly written and the debugger does not help.

автор: Oussama B

Apr 02, 2020

I was really disapointed by this course. Especially the last exercice on imbd faces I absolutely did not understand anything, just copied some code from the VIdeo ....