{ "item_title" : "Adversarial Machine Learning", "item_author" : [" Jaydip Sen "], "item_description" : "This book explores one of the most pressing challenges in artificial intelligence: the vulnerability of learning models to adversarial attacks. It presents a clear overview of how such attacks are crafted and the innovative defenses being developed to counter them. Readers will find a balanced mix of theory and practice, with detailed coverage of both text and image domains. Topics range from saliency-based text manipulation and gradient-driven attacks to ensemble frameworks and meta-learning approaches for defense. The volume also highlights hybrid strategies that combine training and preprocessing methods to improve resilience. A distinctive feature of this work is its dual focus: it examines the evolving techniques of attackers while also offering structured and practical defense strategies. Designed for researchers, practitioners, and students, it provides both conceptual clarity and hands-on insights into a rapidly advancing field. ", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/1/03/647/441/1036474410_b.jpg", "price_data" : { "retail_price" : "132.95", "online_price" : "132.95", "our_price" : "132.95", "club_price" : "132.95", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }

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