Adversarial Learning and Secure AI
shared
This Book is Out of Stock!

About The Book

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.
Piracy-free
Piracy-free
Assured Quality
Assured Quality
Secure Transactions
Secure Transactions
*COD & Shipping Charges may apply on certain items.
Review final details at checkout.
5529
6019
8% OFF
Hardback
Out Of Stock
All inclusive*
downArrow

Details


LOOKING TO PLACE A BULK ORDER?CLICK HERE