GANs

Playing with GANs: Building, coding, and modifying deep learning GAN models | Manning Publications

December 19, 2021

Playing with GANs: Building, coding, and modifying deep learning GAN models | Manning Publications
English | Size: 9.28 GB
Category: Tutorial

Edward explains what are Generative Adversarial Networks (GANs) and demonstrates how to play with GANs by modifying a GAN implementation for new tasks and losses.

Manning – Playing With Gans Building Coding and Modifying Deep Learning Gan Models

December 12, 2021

Manning – Playing With Gans Building Coding and Modifying Deep Learning Gan Models-iLLiTERATE
English | Size: 9.28 GB
Category: Tutorial

Edward explains what are Generative Adversarial Networks (GANs) and demonstrates how to play with GANs by modifying a GAN implementation for new tasks and losses.

Manning – Gans in Action-iLLiTERATE

July 14, 2021

Manning – Gans in Action-iLLiTERATE
English | Size: 2.19 GB
Category: Tutorial

GANs in Action teaches you how to build and train your own Generative Adversarial Networks, one of the most important innovations in deep learning.

Pearson – Machine Vision, GANs, and Deep Reinforcement Learning

April 15, 2021

Pearson – Machine Vision Gans and Deep Reinforcement Learning-iLLiTERATE
English | Size: 10.49 GB
Category: Tutorial

6 Hours of Video Instruction
An intuitive introduction to the latest superhuman capabilities facilitated by Deep Learning.

Addison Wesley Professional Machine Vision GANs and Deep Reinforcement Learning Sneak Peak

March 24, 2020

Addison Wesley Professional Machine Vision GANs and Deep Reinforcement Learning Sneak Peak-XCODE
English | Size: 1.38 GB
Category: Tutorial

An intuitive introduction to the latest superhuman capabilities facilitated by Deep Learning.
Machine Vision, GANs, Deep Reinforcement Learning LiveLessons is an introduction to three of the most exciting topics in Deep Learning today. Modern machine vision involves automated systems outperforming humans on image recognition, object detection, and image segmentation tasks. Generative Adversarial Networks cast two Deep Learning networks against each other in a “forger-detective” relationship, enabling the fabrication of stunning, photorealistic images with flexible, user-specifiable elements. Deep Reinforcement Learning has produced equally surprising advances, including the bulk of the most widely-publicized “artificial intelligence” breakthroughs. Deep RL involves training an “agent” to become adept in given “environments,” enabling algorithms to meet or surpass human-level performance on a diverse range of complex challenges, including Atari video games, the board game Go, and subtle hand-manipulation tasks. Throughout these lessons, essential theory is brought to life with intuitive explanations and interactive, hands-on Jupyter notebook demos. Examples feature Python and straightforward Keras layers in TensorFlow 2, the most popular Deep Learning library.