Description
Generative Adversarial Networks (GAN): The Complete Guide, the Generative Adversarial Networks training course has been published by Udemy Academy. GANs have recently been one of the most interesting developments in deep learning and machine learning. Referring to GANs, Yann LeCun, one of the pioneers of deep learning, said that the most important development in recent years has been adversarial learning. GAN stands for Generative Adversarial Network in which 2 neural networks compete with each other. Unsupervised learning means that we don’t try to map input data to targets, we just try to learn the structure of that input data. This course is a comprehensive guide to Generative Adversarial Networks (GAN). The theories are explained in depth and easily. After each theory lesson, we enter a practical session together. Where we learn how to code different types of GANs in PyTorch and Tensorflow, a very advanced and powerful deep learning framework.
What you will learn
- Learn the basics of generative models
- Build a GAN (Generative Adversarial Network) in TensorFlow
- Tensorflow
- DCGAN
- WGAN
Who is this course suitable for?
- Anyone who wants to improve their deep learning knowledge
Course details Generative Adversarial Networks (GAN): The Complete Guide
- Publisher: Udemy
- teacher : Hoang Quy La
- English language
- Education level: Intermediate
- Number of courses: 20
- Training duration: 3 hours and 47 minutes
Generative Adversarial Networks (GAN): The Complete Guide chapters
Course prerequisites
- Calculus
- Probability
- Object-oriented programming
- Python coding: if/else, loops, lists, dicts, sets
- Basic deep learning
Pictures
Sample video
Installation guide
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English subtitle
Quality: 720p
download link
File(s) password: www.downloadly.ir
Size
1.36 GB
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