Chevron Left
Вернуться к Building Deep Learning Models with TensorFlow

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

Оценки: 657

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


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!


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:

101–125 из 140 отзывов о курсе Building Deep Learning Models with TensorFlow

автор: Gherbi H

17 янв. 2020 г.

The Course was more about the the types of neural networks and how they work than Tensorflow, except for week 1 where we had a Tensorflow introduction, I could gather a lot from the programming assignments but I think there needs to be more about the Tensorflow library in the lectures.

автор: Yong S

6 февр. 2020 г.

I found the practice notebooks of this course to be lacking due to two reasons: 1) The notebook links are broken, resulting in my not being able to complete them. 2) The notebooks do not have practice sections where we could code ourselves following the examples given.

автор: Philippe G

16 мар. 2020 г.

The course is good, but 1) the lab environment is not working at all.... I had to run the notebooks on google colab ! 2) The code is outdated. Tensorflow 2.x is out.

автор: Charles L

23 янв. 2020 г.

Overall good course but lectures were a bit weak on underlying math, compared to labs which made it a challenging at times to tie the two parts together.

автор: Gopal I

14 апр. 2022 г.

One of the better courses in the IBM AI certificate. The notebooks are nicely annotated and have more relevant information than the video lectures.

автор: Mitchell H

6 авг. 2020 г.

All the code is TensorFlow1, which is unfortunately completely outdated. Also no assignments or final. But good for the fundamentals of TF.

автор: Alistair K

11 июня 2020 г.

Basic level but well explained, useful notebooks, not much on Tensorflow, more on the theory of the networks. Uses outdated Tensorflow v1

автор: Alexander S

27 мая 2020 г.

The course is good but you have to change the codes from TF1 to TF2 since is dificult for the learner tranaslate de codes by himself

автор: I'm M

16 апр. 2021 г.

I do not consider the practical part to be exactly beginner level, but the theoretical material is very good.

автор: Jesus S d J

12 июля 2020 г.

Labs would need to be updated to new versions of Tensorflow

The presentations were clear and concise

автор: jordi p c

9 июня 2020 г.

There is a sense to be outdated. Not much activity in the forum, code which is not updated...

автор: Md S A

1 февр. 2022 г.

It would be better if the exams are a bit more tough.

The questions are too easy to solve.

автор: Benhur O

30 янв. 2020 г.

Too focus in coding but not in the underlying concepts and how to use the libraries.

автор: Jochen G

8 февр. 2020 г.

Interesting view on tensor flow, but gap between labs and videos is quite big.

автор: suman k s

19 мая 2020 г.

Low explanation.

But in this short duration we can't expect more.

автор: Giorgio G

25 июня 2020 г.

Course needs to be updated to Tensorflow 2.0 at least.

автор: Sanjeev G

10 мая 2022 г.

we should have more videos and theory also..

автор: Chris R

15 авг. 2022 г.

Material excellent, cramed though.

автор: Kabila H

17 мая 2020 г.

The tensorflow version is outdated

автор: Rafi J O

12 июля 2020 г.

Outdated and not in depth enough.

автор: Emanuel N

23 февр. 2021 г.

Falto mas teoria

автор: Bernardo A P

26 авг. 2020 г.

No real dataset


2 июня 2020 г.

no applications

автор: Juho H

12 мая 2020 г.

Disappointing stuff. The videos teach complex stuff like recurrent neural networks (RNNs like LTSM), restricted Boltzmann machines, and autoencoders very quickly - less than 10 minutes per "week" of learning. While the labs are extensive, you don't learn anything as the amount of TensorFlow code is totally intimidating and none of the steps are really explained. You can copy the code, but you won't develop an understanding of it in this course. Not to mention the code is so heavy the Skills Lab times out before the network is trained. Still, if you just want to claim you've done Tensorflow, you can click through the stuff in about 30 minutes per "week" of learning.

автор: Junsoo P

22 сент. 2020 г.

The lectures only cover various neural nets and not how to actually implement them on Tensorflow, which should be the gist of the course. Further, the labs are at many places not compatible with the most recent Tensorflow version 2's, and only work for previous Tensorflow version 1's which are quite different. The labs must be re-written for the newest versions given Tensorflow's backward incompatibility.