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Computer Science - Adversarial Learning and Secure AI

Description

Book Synopsis: Providing a logical framework for student learning, this is the first textbook on adversarial learning. It introduces vulnerabilities of deep learning, then demonstrates methods for defending against attacks and making AI generally more robust. To help students connect theory with practice, it explains and evaluates attack-and-defense scenarios alongside real-world examples. Feasible, hands-on student projects, which increase in difficulty throughout the book, give students practical experience and help to improve their Python and PyTorch skills. Book chapters conclude with questions that can be used for classroom discussions. In addition to deep neural networks, students will also learn about logistic regression, naïve Bayes classifiers, and support vector machines. Written for senior undergraduate and first-year graduate courses, the book offers a window into research methods and current challenges. Online resources include lecture slides and image files for instructors, and software for early course projects for students.

Details

Looking to take your AI skills to the next level? Dive into the world of adversarial learning with our groundbreaking textbook! Designed to be the first of its kind, this book provides a comprehensive introduction to the vulnerabilities of deep learning and equips you with the tools to defend against attacks. Don't just be a consumer of AI technology, become a master of it.

In the current digital age, the need for robust AI solutions has never been greater. Our book not only explains the theoretical concepts of adversarial learning but also incorporates real-world examples to help you bridge the gap between theory and practice. It's a hands-on learning experience that will elevate your Python and PyTorch skills to new heights.

What sets our textbook apart is its practical approach. As you progress through the chapters, you'll encounter project assignments that gradually increase in difficulty. These assignments simulate real-life attack-and-defense scenarios, allowing you to apply your newly acquired knowledge in a tangible way. Prepare to be amazed at how quickly you can implement your learnings and develop a deep understanding of potential vulnerabilities.

Not only is this book tailored for senior undergraduate and first-year graduate courses, but it also opens the door to cutting-edge research methods and current challenges. Gain insights from the frontiers of AI and set yourself apart as someone who is ahead of the curve. With our online resources, including lecture slides and software for early projects, you'll have everything you need to excel in your academic journey and beyond.

Don't miss out on this opportunity to become an expert in adversarial learning and secure AI. Take the first step towards mastering AI by ordering your copy of Adversarial Learning and Secure AI today. Unleash your full potential and redefine the future of AI with confidence.

Disclosure: I get commissions for purchases made through links in this website