SKU: 90070135895

empire derby cover 25701179

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Description

empire derby cover 25701179Erhhen Sie den Einsatz. Gefrste Highlights zeigen glnzendes Billet Aluminium unter der satten schwarz eloxierten Oberflche, whrend tiefe Rillen jedem Bauteil dieser kompletten Motorabdeckungskollektion auffllige Tiefe und Details verleihen. Die Black Machine Cut Empire Kollektion besteht aus langlebigem Guss und Billet Aluminium und bietet faszinierende individuelle Details, die schwarze oder maschinengeschnittene Zubehrteile ergnzen. Schwarzes

Erhöhen Sie den Einsatz. Gefräste Highlights zeigen glänzendes Billet-Aluminium unter der satten schwarz eloxierten Oberfläche, während tiefe Rillen jedem Bauteil dieser kompletten Motorabdeckungskollektion auffällige Tiefe und Details verleihen. Die Black Machine Cut Empire™-Kollektion besteht aus langlebigem Guss- und Billet-Aluminium und bietet faszinierende individuelle Details, die schwarze oder maschinengeschnittene Zubehörteile ergänzen.
• Schwarzes maschinengeschnittenes Finish
• Eingelassenes klassisches Harley-Davidson-Branding
• Passend zu den Originalkomponenten konzipiert für eine perfekte Passform
• Fügen Sie die komplette Sammlung hinzu oder beginnen Sie mit einer Komponente und bauen Sie Ihr individuelles Fahrzeug

Passend für FLSB ab '18 und Softail-Modelle ab '19. Passt auch für Softail-Modelle '18 mit Narrow Profile Primary Cover P/Ns 25701077, 25700913, 25700937, 25700941, 25701039, 25701040 und 25701043.

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SKU: 90070135895

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4.8 ★★★★★
Based on 27 reviews
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Verified Purchase
TheTechGuyz
Birmingham, US
★★★★★ 5
A good book for Cyber Professionals
Format: Paperback
A very good book, I absolutely love how it gives security professionals much needed AI security insights.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on January 16, 2026
S
Verified Purchase
Steve Wilson
Phoenix, US
★★★★★ 5
In-depth and highly technical!
Format: Paperback
"Adversarial AI Attacks, Mitigations, and Defense Strategies" by John Sotiropoulos is a must-have resource for cybersecurity professionals navigating the complexities of AI security. This book is an incredibly in-depth guide that tackles the intricate details of defending AI systems from adversarial attacks. It’s highly technical, making it an excellent choice for those with a solid background in cybersecurity, machine learning, and system administration. Sotiropoulos doesn’t shy away from the details, providing comprehensive code examples, system admin settings, and scripts that are invaluable for practical implementation. One of the standout aspects of this book is its coverage of both predictive and generative AI. This dual focus ensures that readers are well-equipped to handle security challenges across different AI applications. Whether you're dealing with machine learning models in a predictive context or exploring the relatively newer field of generative AI, this book has you covered. If you’re looking for a technical, hands-on approach to securing AI systems, this book is an essential addition to your library.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on August 12, 2024
N
Verified Purchase
Niti Sharma
Fort Morgan, US
★★★★★ 4
Good and thorough!
Format: Paperback
I was amazed to see a thick book arriving in the package and spent quite some time reading this. The book is so hands-on. I build agentic systems at work and going through these concepts felt good. My only complaint is that the code snippets are not up to date for which I had to edit my code several times.
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Reviewed in the United States on May 9, 2026
C
Verified Purchase
Catalina J.
Massapequa, US
★★★★★ 5
Amazing book
Format: Paperback
Excelent product
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on November 4, 2025
B
Verified Purchase
Brian
New York, US
★★★★★ 5
solid read with walk through
Format: Paperback
There is limited material on this topic and I am about 4 chapters in and I have enjoyed the walkthrough on setting up a lab as the background... will update as I continue through the book.
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Reviewed in the United States on October 18, 2024

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