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Вернуться к Building Deep Learning Models with TensorFlow

Отзывы учащихся о курсе Building Deep Learning Models with TensorFlow от партнера IBM Skills Network

4.4
звезд
Оценки: 652
Рецензии: 135

О курсе

The majority of data in the world is unlabeled and unstructured. Shallow neural networks cannot easily capture relevant structure in, for instance, images, sound, and textual data. Deep networks are capable of discovering hidden structures within this type of data. In this course you’ll use TensorFlow library to apply deep learning to different data types in order to solve real world problems. Learning Outcomes: After completing this course, learners will be able to: • explain foundational TensorFlow concepts such as the main functions, operations and the execution pipelines. • describe how TensorFlow can be used in curve fitting, regression, classification and minimization of error functions. • understand different types of Deep Architectures, such as Convolutional Networks, Recurrent Networks and Autoencoders. • apply TensorFlow for backpropagation to tune the weights and biases while the Neural Networks are being trained....

Лучшие рецензии

ZR

2 июля 2020 г.

Deep Learning made me feel that there is a way to build models and classify data so easily and in a skillful way. Amazing course!

DO

26 мая 2020 г.

Not so often i wish a course would be longer and more in depth I really enjoyed using TF I'll look some other courses about it

Фильтр по:

76–100 из 139 отзывов о курсе Building Deep Learning Models with TensorFlow

автор: Julien P

18 июня 2020 г.

Excellent notebooks. I don't give 5 stars because the quality of videos could be improved and the quizzes could be made tougher. It is easy to pass the class with a superficial understanding of concepts.

автор: RICARDO H R

25 июля 2020 г.

Nice course to introduce you to more advanced neural network algorithms, I wish the evaluations were more challenging and based on practical exercises... there is no final assignment either.

автор: Hrushit J

18 мая 2020 г.

It would have been nice if the video tutorials would explain the code section as well, and if there would have been some in-depth teaching of the code part. But this course did benefit.

автор: Jesus M G G

24 янв. 2020 г.

Videos are good, but the code is more complex than other courses and it needs better description of what is happening, or less complicated code

автор: Ronan C

15 мая 2020 г.

Good an simple videos to understand the concept. The notebooks are very detailed and give a second layer of knowledge with practical example

автор: Xiaoer H

30 июня 2020 г.

The course concepts are not in-depth enough, and the server for Jupyter notebook running is way too slow...

автор: Tariq J

24 февр. 2022 г.

I expected some more explaination for the concepts. However from tensorflow website, more could be learnt.

автор: Projit C

1 апр. 2020 г.

The coding part was hard to understand. If that part could also be covered in videos as a tutorial.

автор: Panos K

5 июня 2022 г.

Great introduction to unsupervised learning. However its an easy course with not much to offer

автор: Javier R

17 июля 2020 г.

It would be grate that the examples have been updated to the TF 2.0 version.

автор: Kaosara B

5 авг. 2022 г.

i loved it. I have an undertsanding of different deep learning models

автор: srivikram m

5 июня 2022 г.

Was a really fun course, but the final assignments were very lengthy.

автор: Patricio V

1 июня 2020 г.

Good material but almost all the labs are too slow to run properly

автор: Vishwanathan C

21 апр. 2020 г.

Good introduction to Deep Learning Models with Tensorflow

автор: Tim d Z

24 мар. 2020 г.

Very informative, could use some more room for practice.

автор: Mahesh N

1 мая 2020 г.

Lab content must be updated with latest TensorFlow.

автор: Armen M

25 мар. 2020 г.

Thank you. thought it's could be more deeper

автор: Mpho c

7 янв. 2020 г.

no audio in the last learning unit 5.

автор: TIANYU S

26 мая 2020 г.

some questions are a bit confusing

автор: Bhaskar N S

4 апр. 2020 г.

Met expectations

автор: konutek

2 февр. 2020 г.

It is ok

автор: Nagesh R

8 июня 2020 г.

good

автор: Roger S P M

4 апр. 2020 г.

This is a pretty good course on the different types of neural networks and their cousins. The presentation slides are really well done. The examples are programmed in TensorFlow. But the course does not really teach very much about TensorFlow itself. The opening lecture on TF describes it in terms that suggest this was created for TF 1.x, rather than the new structure in 2.x. But that turns out not to be an issue since they go into little detail on TF itself.

The programming examples are really good. However, most of the time, the CognitiveCourse.ai web site on which they run is usually not working. So you often cannot use the labs in conjunction with the lectures. You have to go back and access the labs sometime when the website is working.

автор: Michael C

10 сент. 2020 г.

While the lab and videos explained the concepts really well, the codes from the labs are outdated. They are using tensorflow version 1, while tensorflow version 2 (current version) is very different. I have to go outside of this course to learn the new codes.

Other than that, every other aspect of the course is good. explanations are clear, videos and diagrams are very detail. Just the right amount of labs etc

автор: Simon P

17 окт. 2020 г.

Lots of code and theory heavy, which is not a bad thing, but there is little thought given over to the actual learning objectives. There is also no real opportunity to practice learning to use TensorFlow. There are likely better tutorials out there, which is a shame because a lot of effort has gone into this course.