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Opiniones y comentarios de aprendices correspondientes a Building Deep Learning Models with TensorFlow por parte de IBM

4.3
estrellas
447 calificaciones
94 revisiones

Acerca del 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....

Principales revisiones

ZR

Jul 03, 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

May 27, 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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51 - 75 de 94 revisiones para Building Deep Learning Models with TensorFlow

por Hrushit J

May 18, 2020

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.

por Jesus M G G

Jan 24, 2020

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

por Ronan C

May 15, 2020

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

por Xiaoer H

Jun 30, 2020

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

por Projit C

Apr 01, 2020

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

por Javier R V

Jul 17, 2020

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

por Patricio V

Jun 02, 2020

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

por Vishwanathan C

Apr 21, 2020

Good introduction to Deep Learning Models with Tensorflow

por Tim d Z

Mar 24, 2020

Very informative, could use some more room for practice.

por N M

May 01, 2020

Lab content must be updated with latest TensorFlow.

por Armen M

Mar 25, 2020

Thank you. thought it's could be more deeper

por Mpho c

Jan 07, 2020

no audio in the last learning unit 5.

por TIANYU S

May 26, 2020

some questions are a bit confusing

por Bhaskar N S

Apr 04, 2020

Met expectations

por Konrad A B

Feb 02, 2020

It is ok

por Nagesh R

Jun 08, 2020

good

por Roger S P M

Apr 05, 2020

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.

por Gherbi H

Jan 17, 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

Feb 07, 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

Mar 16, 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

Jan 24, 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 Mitchell H

Aug 07, 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

Jun 11, 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

May 27, 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 Jesus S d J

Jul 12, 2020

Labs would need to be updated to new versions of Tensorflow

The presentations were clear and concise