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Voltar para Building Deep Learning Models with TensorFlow

Comentários e feedback de alunos de Building Deep Learning Models with TensorFlow da instituição IBM Skills Network

4.4
estrelas
652 classificações
135 avaliações

Sobre o curso

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....

Melhores avaliações

ZR

2 de jul de 2020

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 de mai de 2020

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

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101 — 125 de 139 Avaliações para o Building Deep Learning Models with TensorFlow

por Gherbi H

17 de jan de 2020

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.

por Yong S

6 de fev de 2020

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.

por Philippe G

16 de mar de 2020

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 I had to run the notebooks on google colab ! 2) The code is outdated.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.

por Charles L

23 de jan de 2020

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.

por Gopal I

14 de abr de 2022

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

por Mitchell H

6 de ago de 2020

All the code is TensorFlow1, which is unfortunately completely outdated.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

por Alistair K

11 de jun de 2020

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 Uses outdated Tensorflow v1

por Alexander S

27 de mai de 2020

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

por I'm M

16 de abr de 2021

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

por Jesus S d J

12 de jul de 2020

Labs would need to be updated to new versions of Tensorflow

The presentations were clear and concise

por jordi p c

9 de jun de 2020

There is a sense to be outdated.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

por Md S A

1 de fev de 2022

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

The questions are too easy to solve.

por Benhur O

30 de jan de 2020

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

por Jochen G

8 de fev de 2020

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

por suman k s

19 de mai de 2020

Low explanation.

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

por Giorgio G

25 de jun de 2020

Course needs to be updated to Tensorflow 2.0 at least.

por Sanjeev G

10 de mai de 2022

we should have more videos and theory also..

por Kabila H S

17 de mai de 2020

The tensorflow version is outdated

por Rafi J O

12 de jul de 2020

Outdated and not in depth enough.

por Emanuel N

23 de fev de 2021

Falto mas teoria

por Bernardo A P

26 de ago de 2020

No real dataset

por ABOUJAAFAR O

2 de jun de 2020

no applications

por Juho H

12 de mai de 2020

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.

por Junsoo P

22 de set de 2020

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.

por Dean E B

26 de abr de 2022

Weakest of the IBM series I took. Problems with labs working. No response from questions on forums. A very shallow presentation of fairly deep subject matter. Very little background or use of TensorFlow.