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Вернуться к Building Deep Learning Models with TensorFlow

Отзывы учащихся о курсе Building Deep Learning Models with TensorFlow от партнера IBM Skills Network

4.4
звезд
Оценки: 656

О курсе

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....

Лучшие рецензии

ZR

2 июля 2020 г.

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 мая 2020 г.

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

Фильтр по:

126–140 из 140 отзывов о курсе Building Deep Learning Models with TensorFlow

автор: Dean E B

26 апр. 2022 г.

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.

автор: Stefan L

4 июля 2020 г.

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 however the code is SEVERELY out of date.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

автор: Farrukh N A

13 янв. 2020 г.

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

автор: Pakawat N

31 мая 2020 г.

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

автор: Sowmyashree S

2 мая 2020 г.

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

автор: César A C

29 июня 2020 г.

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

автор: Eric

30 янв. 2020 г.

Way too short in terms of the amount of content

автор: Julian S

21 июня 2020 г.

The Material needs to be updated!

автор: Ustinov A

6 авг. 2020 г.

Good videos and bad labs. An old TensorFlow version is used. Therefore all code is useless for the current version of TensorFlow (ver. 2). It had to become the most important part of the specialization for me... There are a lot of topics about problems on the forum. And it's strange that IBM can't change it for a half year.

автор: Onno v E

24 авг. 2020 г.

This course is very outdated, it needs to be updated to Tensor Flow 2.0.

There are NO EXERCISES at all, only labs that contain the some content as the video's. I don't think I really learned much during this course, as the course does not dive deep into the models selected for the course.

автор: Huang-Hsiang L

12 сент. 2021 г.

The lecture is very horrible and you almost need to learn all the details about tensorflow by yourself, which does not make sense. The lecture should explain those details in a clear and easy-to-understand way so that student can benefit.

автор: Anas O

2 июня 2020 г.

the labs are based on an outdated tensorflow version, also, the instructor is not Alex Akilson as it is mentioned in the course info.

автор: Martin

13 июня 2020 г.

All the code in the course is obsolete using an old version of TF. The course does not have a project nor a final assignment.

автор: Sumika M

1 мар. 2022 г.

Very badly designed. Code written in the labs is very hard to understand

автор: Haimanot B

27 мар. 2022 г.

I get some basic Idea about deep learning