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

4.3
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189 calificaciones
36 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

LD

Nov 06, 2019

course needed to be updated for labs. Now Google moved to Tensorflow 2.0 this year.

SA

Feb 04, 2020

It helped me to understand how TensorFlow can be used to build the neural networks

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26 - 36 de 36 revisiones para Building Deep Learning Models with 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 Konrad A B

Feb 02, 2020

It is ok

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 Benhur O J

Jan 30, 2020

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

por Jochen G

Feb 08, 2020

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

por 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.

por Eric

Jan 30, 2020

Way too short in terms of the amount of content