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Building Deep Learning Models with TensorFlow(으)로 돌아가기

IBM의 Building Deep Learning Models with TensorFlow 학습자 리뷰 및 피드백

4.1
stars
98개의 평가
18개의 리뷰

강좌 소개

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....

최상위 리뷰

필터링 기준:

Building Deep Learning Models with TensorFlow의 18개 리뷰 중 1~18

교육 기관: Lam C V D

Nov 06, 2019

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

교육 기관: Shinhoo K

Nov 17, 2019

The codes need to be updated for TensorFlow 2.0.

교육 기관: Theodore G

Jan 11, 2020

This course is incomplete, and is NOT recommended.

It uses Tensorflow 1, which is outdated now - should be updated to use Tensorflow 2.

It does not provide practice sessions.

Week 5 - Autoencoder - have no audio, no captions, nothing.

There is no final exam to ensure our competence. No labs we need to be graded on.

This is not a worthy Coursera course. It needs to be withdrawn and updated.

교육 기관: Tony H

Nov 18, 2019

Mostly trivial quiz questions and no graded practical work. The certificate is therefore not worth very much.

교육 기관: Martin K

Nov 22, 2019

Good content. A bit too fast on some complex concepts and missing audio for the last lecture but great lecturer.

교육 기관: Nopthakorn K

Dec 31, 2019

Week 5 lecture video no audio

Lab is not update for tensorflow 2

교육 기관: RuoxinLi

Dec 14, 2019

some audios are missing

교육 기관: Phillip R

Dec 19, 2019

needs to be updated for tensorflow 2 and the last videos were missing sound

교육 기관: Renan B F

Dec 08, 2019

Material from the last 2 weeks aren't comparable to other weeks.

교육 기관: John R H A

Dec 07, 2019

Teaches more on Deep Learning models but less in TensorFlow

교육 기관: Tristan S

Jan 09, 2020

This course is a joke. It's a brief overview of a few types of models. Also there is no sound in half the videos.

교육 기관: Oliver M

Jan 02, 2020

Lack of content, quizzes were poor, no sound or transcript on 2 videos. Took about 2 hours total.

교육 기관: dk

Nov 26, 2019

这什么课?即没多少Deep Learning

的内容,也没多少TENSORFLOW的内容?

교육 기관: James R

Dec 22, 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.

교육 기관: Pietro D

Jan 05, 2020

Very clear explanation and well organized course. I give 4 stars because videos of Week 5 are missing the audio and subtitles.

교육 기관: Mpho c

Jan 07, 2020

no audio in the last learning unit 5.

교육 기관: 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.

교육 기관: 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.