Udemy – Generative Adversarial Networks (GAN): The Complete Guide 2022-3
Udemy – Generative Adversarial Networks (GAN): The Complete Guide 2022-3 Downloadly IRSpace
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Generative Adversarial Networks (GAN): The Complete Guide, GANs have been one of the most interesting developments in deep learning and machine learning recently. Yann LeCun, a deep learning pioneer, has said that the most important development in recent years has been adversarial training, referring to GANs. GAN stands for generative adversarial network, where 2 neural networks compete with each other. Unsupervised learning means we’re not trying to map input data to targets, we’re just trying to learn the structure of that input data. This course is a comprehensive guide to Generative Adversarial Networks (GANs). The theories are explained in-depth and in a friendly manner. After each theoretical lesson, we will dive together into a hands-on session, where we will be learning how to code different types of GANs in PyTorch and Tensorflow, which is a very advanced and powerful deep learning framework!
What you’ll learn
- Learn the basic principles of generative models
- Build a GAN (Generative Adversarial Network) in Tensorflow
- Tensorflow
- DCGAN
- WGAN
Who this course is for
- Anyone who wants to improve their deep learning knowledge
Specificatoin of Generative Adversarial Networks (GAN): The Complete Guide
- Publisher : Udemy
- Teacher : Hoang Quy La
- Language : English
- Level : Intermediate
- Number of Course : 20
- Duration : 3 hours and 47 minutes
Content of Generative Adversarial Networks (GAN): The Complete Guide
Requirements
- Calculus
- Probability
- Object-oriented programming
- Python coding: if/else, loops, lists, dicts, sets
- Basic deep learning
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Subtitle : English
Quality: 720p
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File size
1.36 GB
