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

505 calificaciones
106 reseña

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 reseñas

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!

26 de may. 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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51 - 75 de 106 revisiones para Building Deep Learning Models with TensorFlow

por A A A

7 de jul. de 2020

The instructor Saeed Aghabozorgi did an excellent job in explaining the concepts in a way everything can be understood easily. However, I still think 5 weeks is not enough for this course, given TensorFlow is more difficult to learn than PyTorch. The basics could be covered in more detail, including the tf.get_variable(), tf.gradient(), calculating gradients and other functions that were used. There could be a lecture for Linear Regression and Logistic Regression and these 2 could be moved to a separate week instead. Also, please upgrade the code to work on TensorFlow 2.1. The current code designed for TensorFlow 1.8 didn't work especially the part where datasets are to be loaded.

por bob n

15 de oct. de 2020

Four stars because some of the labs (and none of the lectures) have not been brought up to the current version of TensorFlow. There are significant differences between 1.x and 2.x, especially in the paralell processing. I don't expect a course to send me on wild goose chases across the internet having to bring their examples up to current versions. I guess you get what you pay for, no surprise that Big Blue isn't current.

por Michael S

26 de mar. de 2020

Very interesting material, and easy to follow along. The notebooks are a great resource. I am glad to have been introduced to these concepts. However, I felt this course was too easy and it did not encourage the student to complete projects or any independent work. In any case, this course was worth taking.

por James R

22 de dic. de 2019

I liked the course; however, there was no sound or transcripts for the last week of the course. This required me to research all the topics that I saw on the screen. Still a good learning experience but put more responsibility on me to learn the topics.

por Edward J

20 de oct. de 2020

Interesting course but I wish there were more opportunities to add code myself or even a proper task. I was sad not to have videos from Romeo. However, I thought that the explanations of the different deep learning models were very clear.

por Julien P

18 de jun. de 2020

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.


25 de jul. de 2020

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.

por Hrushit J

18 de may. de 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

24 de ene. de 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

15 de may. de 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

30 de jun. de 2020

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

por Projit C

1 de abr. de 2020

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

por Javier R V

17 de jul. de 2020

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

por Patricio V

1 de jun. de 2020

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

por Vishwanathan C

21 de abr. de 2020

Good introduction to Deep Learning Models with Tensorflow

por Tim d Z

24 de mar. de 2020

Very informative, could use some more room for practice.

por Mahesh N

1 de may. de 2020

Lab content must be updated with latest TensorFlow.

por Armen M

25 de mar. de 2020

Thank you. thought it's could be more deeper

por Mpho c

7 de ene. de 2020

no audio in the last learning unit 5.


26 de may. de 2020

some questions are a bit confusing

por Bhaskar N S

4 de abr. de 2020

Met expectations

por Konrad A B

2 de feb. de 2020

It is ok

por Nagesh R

8 de jun. de 2020


por Roger S P M

4 de abr. de 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 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 Michael C

10 de sep. de 2020

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