Chevron Left
Вернуться к Data Pipelines with TensorFlow Data Services

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

4.4
звезд
Оценки: 413
Рецензии: 89

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 will: - Perform streamlined ETL tasks using TensorFlow Data Services - Load different datasets and custom feature vectors using TensorFlow Hub and TensorFlow Data Services APIs - Create and use pre-built pipelines for generating highly reproducible I/O pipelines for any dataset - Optimize data pipelines that become a bottleneck in the training process - Publish your own datasets to the TensorFlow Hub library and share standardized data with researchers and developers around the world 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

PC
16 апр. 2020 г.

I understand why most of the students are furious about, but content wise, it one of those extremely helpful and important courses in Coursera. Really loved it!

GL
2 мар. 2020 г.

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

Фильтр по:

51–75 из 89 отзывов о курсе Data Pipelines with TensorFlow Data Services

автор: Levina A

24 мая 2021 г.

So cool

автор: Mellania P S

18 мая 2021 г.

AMAZING

автор: Indah D S

8 мая 2021 г.

great

автор: Al F N P M

29 мая 2021 г.

Nice

автор: Ahmad H N

29 апр. 2021 г.

Good

автор: 林韋銘

16 июня 2020 г.

GJ

автор: Cees R

24 мар. 2020 г.

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: Matej M

16 мар. 2021 г.

This course was much better than the two before. Here were real exercises you had to do. It was not just about watching the videos. Topic itself was kind of boring. But the quality much better than others. Also on the discussion forum you were able to search for help.

автор: Yopi P O

17 мая 2020 г.

Debugging exercises due to errors in indentation sounded stupid in the first place. But the joy of finally getting a "yes" in the assignment auto-grader beats them all.

автор: Vinay M

5 июня 2020 г.

Was not that much engaging because the lectures were not linked properly and were lacking examples to support the content

автор: Ruan V

18 авг. 2020 г.

Excellent content, but the design of Exercise 4 tainted the experience somewhat by the end.

автор: Gregor S

3 февр. 2021 г.

Great explanation, however I believe in Week3 there are some broken links . . .heart.csv

автор: Jobaer C

27 авг. 2020 г.

Would be a 5-start if the last assignment was a bit well thought out.

автор: Mario A C S

16 сент. 2020 г.

Last week exercise is problematic and not that educational

автор: Chow K M

10 авг. 2020 г.

Coding exercises were generally straightforward.

автор: Elyasaf E

7 апр. 2021 г.

More and better explanations are needed

автор: Chuong L

16 апр. 2020 г.

week 4 wasn't very clear

автор: Yong M L

24 сент. 2020 г.

This course is really interesting during the start, because there are a lot of hands-on for us to play around with the code. It shows the capability of TensorFlow as a Machine Learning framework which can also be used for data preprocessing before the model training.

However, the Assignments were very poorly designed in my opinion. I relied heavily on the discussion forums to pass the Assignments. It seems like a bug to me when you need to navigate through the Jupyter workspace to find the Week 5 notebook, then modify the codes from there and submit it to pass the Week 4 assignment.

автор: İlkin H

30 июля 2020 г.

Course content deserves 5 starts. Really nice and very useful tutorial. But assignments are not as good as the content. There are very less explanation , many mistakes ( specially at the last assignment, because of typo, you may submit several times) , no expected outcome to control before submitting (evaluation time of third assignment took around 30 minutes for me).

автор: Vincent H

14 апр. 2020 г.

The content of weeks 1 to 3 is very useful and the videos are clear. However the content of week 4 goes way to fast, and the last exercice is way more difficult to do, and to validate. The number of questions in the forum on that matter illustrates that something could be improve. Though, thanks for the course!

автор: Moustafa S

3 июля 2020 г.

too much informations but for the most part it's made for the researchers, dealing with so many complicated methods and functions in tensorflow, which was helpful but the codes were too much and not described indepth, maybe you can improve the way you showcase the codes slowly and in different senarios.

автор: Parth J

3 июня 2020 г.

A lot of information was crammed in videos of very short duration. The course could have been more comprehensive. Also, a detailed explanation of errors on making wrong submissions would be very helpful.

автор: Marko N

13 сент. 2020 г.

Currently the assignments are broken and it takes a lot of effort to successfully complete them because of that. Hopefully they fix it in the future.

автор: András G

17 февр. 2020 г.

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

автор: Shobhit G

16 мая 2020 г.

Last Assignment does not have proper logs and instructions.