Tag: Adversarial

Introduction to Generative Adversarial Networks (GANs)

Free Download Introduction to Generative Adversarial Networks (GANs)
Released: 03/2023
Duration: 29m | .MP4 1280×720, 30 fps(r) | AAC, 48000 Hz, 2ch | 319 MB
Level: Beginner | Genre: eLearning | Language: English
Recently, you’ve probably seen the impacts of large-scale generative art, generative text, and generative movies. Do you want to understand the basics of how this type of AI works? In this course, Martin Kemka, founder of the machine learning production house Northraine, introduces you to a very important component in the world of generative AI: Generative Adversarial Networks (GANs). Learn about the history of GANs, including where they came from and how they changed over the last decade. Find out how to train a model as you examine the model architecture and how the structure of multiple models works together. Get hands-on experience training a simple model in Jupyter Notebook. Plus, get insights on the current state of GAI and thoughts on where it’s going next.


Adversarial Deep Learning in Cybersecurity Attack Taxonomies, Defence Mechanisms, and Learning Theories

Free Download Aneesh Sreevallabh Chivukula, "Adversarial Deep Learning in Cybersecurity: Attack Taxonomies, Defence Mechanisms, and Learning Theories"
English | ISBN: 3030997715 | 2023 | 319 pages | PDF | 3 MB
A critical challenge in deep learning is the vulnerability of deep learning networks to security attacks from intelligent cyber adversaries. Even innocuous perturbations to the training data can be used to manipulate the behaviour of deep networks in unintended ways. In this book, we review the latest developments in adversarial attack technologies in computer vision; natural language processing; and cybersecurity with regard to multidimensional, textual and image data, sequence data, and temporal data. In turn, we assess the robustness properties of deep learning networks to produce a taxonomy of adversarial examples that characterises the security of learning systems using game theoretical adversarial deep learning algorithms. The state-of-the-art in adversarial perturbation-based privacy protection mechanisms is also reviewed.


Adversarial Machine Learning

Adversarial Machine Learning by Yevgeniy Vorobeychik
English | August 8, 2018 | ISBN: 1681733951 | 172 pages | PDF (Converted) | 5.59 Mb
This is a technical overview of the field of adversarial machine learning which has emerged to study vulnerabilities of machine learning approaches in adversarial settings and to develop techniques to make learning robust to adversarial manipulation.