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Learner Reviews & Feedback for Building Deep Learning Models with TensorFlow by IBM

4.4
stars
633 ratings
130 reviews

About the Course

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....

Top reviews

ZR

Jul 2, 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 26, 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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76 - 100 of 134 Reviews for Building Deep Learning Models with TensorFlow

By 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.

By 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

By 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

By Xiaoer H

Jun 30, 2020

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

By Tariq J

Feb 24, 2022

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

By Projit C

Apr 1, 2020

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

By Javier R

Jul 17, 2020

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

By Patricio V

Jun 1, 2020

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

By Vishwanathan C

Apr 21, 2020

Good introduction to Deep Learning Models with Tensorflow

By Tim d Z

Mar 24, 2020

Very informative, could use some more room for practice.

By Mahesh N

May 1, 2020

Lab content must be updated with latest TensorFlow.

By Armen M

Mar 25, 2020

Thank you. thought it's could be more deeper

By mpho c

Jan 7, 2020

no audio in the last learning unit 5.

By TIANYU S

May 26, 2020

some questions are a bit confusing

By Bhaskar N S

Apr 4, 2020

Met expectations

By konutek

Feb 2, 2020

It is ok

By Nagesh R

Jun 8, 2020

good

By Roger S P M

Apr 4, 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.

By Michael C

Sep 10, 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

By Simon P

Oct 17, 2020

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.

By 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.

By Yong S

Feb 6, 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.

By 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.

By Charles L

Jan 23, 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.

By Gopal I

Apr 14, 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.