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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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101 - 125 of 134 Reviews for Building Deep Learning Models with TensorFlow

By Mitchell H

Aug 6, 2020

All the code is TensorFlow1, which is unfortunately completely outdated.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

By 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 Uses outdated Tensorflow v1

By 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

By I'm M

Apr 16, 2021

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

By Jesus S d J

Jul 12, 2020

Labs would need to be updated to new versions of Tensorflow

The presentations were clear and concise

By jordi p c

Jun 9, 2020

There is a sense to be outdated.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

By Md S A

Feb 1, 2022

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

The questions are too easy to solve.

By Benhur O

Jan 30, 2020

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

By Jochen G

Feb 8, 2020

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

By suman k s

May 19, 2020

Low explanation.

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

By Giorgio G

Jun 25, 2020

Course needs to be updated to Tensorflow 2.0 at least.

By Sanjeev G

May 10, 2022

we should have more videos and theory also..

By Kabila H S

May 17, 2020

The tensorflow version is outdated

By Rafi J O

Jul 12, 2020

Outdated and not in depth enough.

By Emanuel N

Feb 23, 2021

Falto mas teoria

By Bernardo A P

Aug 26, 2020

No real dataset

By ABOUJAAFAR O

Jun 2, 2020

no applications

By Juho H

May 12, 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.

By Junsoo P

Sep 22, 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.

By Dean E B

Apr 26, 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.

By Stefan L

Jul 4, 2020

This course was very informative and the labs are really well written.... however the code is SEVERELY out of date. It needs to be updated for TensorFlow 2.0, there is simply no excuse at this point

By Farrukh N A

Jan 13, 2020

First of all it was too complex, unlike the course on PyTorch which focused on both Theory + Practical part. It focus only on theory.

By Pakawat N

May 31, 2020

It is too basic and almost no technical detail about the DNN. It is not good for who have basic knowledge about this before.

By Sowmyashree S

May 2, 2020

The codes should be provided with Tensorflow 2.0. Practical implementation should also be shown.

By César A C

Jun 29, 2020

I think that the labs should have been updated to tensorflow 2.