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Generate Synthetic Images with DCGANs in Keras に戻る

Coursera Project Network による Generate Synthetic Images with DCGANs in Keras の受講者のレビューおよびフィードバック

4.5
238件の評価
46件のレビュー

コースについて

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....

人気のレビュー

AA
2020年5月26日

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
2020年6月13日

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

フィルター:

Generate Synthetic Images with DCGANs in Keras: 26 - 46 / 46 レビュー

by SHANKAR

2020年6月14日

Trainer was awesome

by Gangone R

2020年7月4日

very useful course

by Javier F B

2020年4月24日

Excellent course.

by Ayush G

2020年10月6日

nice project

by Umit K

2020年9月9日

Thank you.

by Rajasinghe R

2020年5月28日

very goood

by Santiago G

2020年8月22日

Thanks!

by VETTORI F M

2020年8月30日

easy

by p s

2020年6月23日

Good

by tale p

2020年6月16日

good

by 321810306031 A C H

2020年7月13日

tx

by Ebin Z

2020年6月9日

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.

by Diego P P

2020年6月10日

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

by Svitlana Z

2020年5月5日

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

by Shakshi S

2020年8月6日

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

by Srinadh R B

2020年9月11日

Nice choice to start with the understanding of GANs.

by Deep G

2020年5月21日

Good way to start out implementing DCGANS!!

by sarithanakkala

2020年6月23日

Good

by vijayalode

2020年6月24日

na

by Akshita S

2020年7月26日

A bit overpriced for the amount of knowledge being shared.

by Simon S R

2020年8月31日

Still room for a lot of improvements, average material