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Generate Synthetic Images with DCGANs in Keras(으)로 돌아가기

Coursera Project Network의 Generate Synthetic Images with DCGANs in Keras 학습자 리뷰 및 피드백

4.5
별점
241개의 평가
47개의 리뷰

강좌 소개

In this hands-on project, you will learn about Generative Adversarial Networks (GANs) and you will build and train a Deep Convolutional GAN (DCGAN) with Keras to generate images of fashionable clothes. We will be using the Keras Sequential API with Tensorflow 2 as the backend. In our GAN setup, we want to be able to sample from a complex, high-dimensional training distribution of the Fashion MNIST images. However, there is no direct way to sample from this distribution. The solution is to sample from a simpler distribution, such as Gaussian noise. We want the model to use the power of neural networks to learn a transformation from the simple distribution directly to the training distribution that we care about. The GAN consists of two adversarial players: a discriminator and a generator. We’re going to train the two players jointly in a minimax game theoretic formulation. This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with Python, Jupyter, and Keras pre-installed. Notes: - You will be able to access the cloud desktop 5 times. However, you will be able to access instructions videos as many times as you want. - This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions....

최상위 리뷰

AA

2020년 5월 26일

The course was well equipped. It gave me the basic idea of how GAN works and how to implement it. If you want to get started with GAN then it can be a better course to lead you.

AG

2020년 6월 13일

In this course, you will learn about a lot of different ways to join ideas to make more complex and interesting knowledge of keras

필터링 기준:

Generate Synthetic Images with DCGANs in Keras의 47개 리뷰 중 26~47

교육 기관: SHANKAR

2020년 6월 14일

Trainer was awesome

교육 기관: Gangone R

2020년 7월 4일

very useful course

교육 기관: Javier F B

2020년 4월 24일

Excellent course.

교육 기관: Ayush G

2020년 10월 6일

nice project

교육 기관: Umit K

2020년 9월 9일

Thank you.

교육 기관: Rajasinghe R

2020년 5월 28일

very goood

교육 기관: Santiago G

2020년 8월 22일

Thanks!

교육 기관: VETTORI F M

2020년 8월 30일

easy

교육 기관: p s

2020년 6월 23일

Good

교육 기관: tale p

2020년 6월 16일

good

교육 기관: 321810306031 A C H

2020년 7월 13일

tx

교육 기관: Ebin Z

2020년 6월 9일

Everything was well explained and a very good project to get a good knowledge about GAN networks and its applications. Looking for more such projects.

교육 기관: Diego P P

2020년 6월 10일

I't's a good project, the theory should be more explained but in general was interesting to know about this network

교육 기관: Svitlana Z

2020년 5월 5일

This course helped me to start developing GANs. I would like to hear more theoretical explanations.

교육 기관: Shakshi S

2020년 8월 6일

I tried this project and it is really good if you want to have idea about GANs and DCGANs.

교육 기관: Srinadh R B

2020년 9월 11일

Nice choice to start with the understanding of GANs.

교육 기관: Deep G

2020년 5월 21일

Good way to start out implementing DCGANS!!

교육 기관: sarithanakkala

2020년 6월 23일

Good

교육 기관: vijayalode

2020년 6월 24일

na

교육 기관: Akshita S

2020년 7월 26일

A bit overpriced for the amount of knowledge being shared.

교육 기관: Simon S R

2020년 8월 31일

Still room for a lot of improvements, average material

교육 기관: Zhiqiu L

2022년 2월 10일

The course spends too much time on the coding without explaining the model details.