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Отзывы учащихся о курсе Generate Synthetic Images with DCGANs in Keras от партнера Coursera Project Network

4.5
звезд
Оценки: 232
Рецензии: 45

О курсе

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....

Лучшие рецензии

AA
26 мая 2020 г.

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
13 июня 2020 г.

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

Фильтр по:

26–44 из 44 отзывов о курсе Generate Synthetic Images with DCGANs in Keras

автор: Javier F B

24 апр. 2020 г.

Excellent course.

автор: Ayush G

6 окт. 2020 г.

nice project

автор: umit k

9 сент. 2020 г.

Thank you.

автор: Rajasinghe R

28 мая 2020 г.

very goood

автор: Santiago G

22 авг. 2020 г.

Thanks!

автор: VETTORI F M

30 авг. 2020 г.

easy

автор: p s

23 июня 2020 г.

Good

автор: tale p

16 июня 2020 г.

good

автор: 321810306031 A C H

13 июля 2020 г.

tx

автор: Ebin Z

9 июня 2020 г.

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.

автор: Diego P P

10 июня 2020 г.

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

автор: Svitlana Z

5 мая 2020 г.

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

автор: Shakshi S

6 авг. 2020 г.

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

автор: Srinadh R B

11 сент. 2020 г.

Nice choice to start with the understanding of GANs.

автор: Deep G

21 мая 2020 г.

Good way to start out implementing DCGANS!!

автор: sarithanakkala

23 июня 2020 г.

Good

автор: vijayalode

24 июня 2020 г.

na

автор: Akshita S

26 июля 2020 г.

A bit overpriced for the amount of knowledge being shared.

автор: Simon S R

31 авг. 2020 г.

Still room for a lot of improvements, average material