Chevron Left
Retour à Generate Synthetic Images with DCGANs in Keras

Avis et commentaires pour d'étudiants pour Generate Synthetic Images with DCGANs in Keras par Coursera Project Network

4.5
étoiles
242 évaluations

À propos du cours

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....

Meilleurs avis

AA

26 mai 2020

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 juin 2020

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

Filtrer par :

1 - 25 sur 47 Avis pour Generate Synthetic Images with DCGANs in Keras

par Krishna V D

29 mai 2020

par Saida M D C

25 mai 2020

par DARSHAN D

1 août 2020

par Sai D P

12 juin 2020

par Paras V

31 mai 2020

par Andrea R

13 mai 2020

par Ha Q

22 juin 2020

par Никита А Ф

10 sept. 2020

par Abrar I A

27 mai 2020

par Abhishek P G

14 juin 2020

par David C

20 août 2021

par Sumit A T

21 juil. 2020

par Warunee S

4 juil. 2020

par sunil k s

13 août 2020

par Bappaditya D

4 juin 2021

par Adrien A

21 déc. 2020

par MS. S S

15 août 2020

par Ahmed A

21 mai 2020

par Ali A

19 juin 2020

par Mayank S

1 mai 2020

par Md. S A

6 sept. 2020

par Pratikshya M

2 nov. 2020

par Rishabh R

17 mai 2020

par Vishnu N

18 oct. 2020

par Yuvraj S C

24 sept. 2020