12-01-2023, 02:50 AM
Deep Convolutional Generative Adversarial Networks (DCGAN)
Learn to create Generative Adversarial Networks (GAN) and Deep Convolutional Generative Adversarial Networks (DCGAN)
Rating: 3.5 out of 5
(23 ratings)
2,597 students
2.5 hours on-demand video
3 articles
1 downloadable resource
Description
Generative Adversarial Networks (GANs) and Deep Convolutional Generative Adversarial Networks (DCGAN) are one of the most interesting and trending ideas in computer science today.
Two models are trained simultaneously by an adversarial process. A generator , learns to create images that look real, while a discriminator learns to tell real images apart from fakes.
At the end of the Course you will understand the basics of Python Programming and the basics ofGenerative Adversarial Networks (GANs) and Deep Convolutional Generative Adversarial Networks (DCGAN) .
The course will have step by step guidance
Import TensorFlow and other libraries
Load and prepare the dataset
Create the models (Generator and Discriminator)
Define the loss and optimizers (Generator loss , Discriminator loss)
Define the training loop
Train the model
Analyze the output
https://www.udemy.com/course/deep-convolutional-generative-adversarial-networks-dcgan/?couponCode=ACCC82A67D7A8EDA684C
Enjoy!
Learn to create Generative Adversarial Networks (GAN) and Deep Convolutional Generative Adversarial Networks (DCGAN)
Rating: 3.5 out of 5
(23 ratings)
2,597 students
2.5 hours on-demand video
3 articles
1 downloadable resource
Description
Generative Adversarial Networks (GANs) and Deep Convolutional Generative Adversarial Networks (DCGAN) are one of the most interesting and trending ideas in computer science today.
Two models are trained simultaneously by an adversarial process. A generator , learns to create images that look real, while a discriminator learns to tell real images apart from fakes.
At the end of the Course you will understand the basics of Python Programming and the basics ofGenerative Adversarial Networks (GANs) and Deep Convolutional Generative Adversarial Networks (DCGAN) .
The course will have step by step guidance
Import TensorFlow and other libraries
Load and prepare the dataset
Create the models (Generator and Discriminator)
Define the loss and optimizers (Generator loss , Discriminator loss)
Define the training loop
Train the model
Analyze the output
https://www.udemy.com/course/deep-convolutional-generative-adversarial-networks-dcgan/?couponCode=ACCC82A67D7A8EDA684C
Enjoy!