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Description
Starliner Kofferraumwanne für Mercedes E-Klasse T-Modell Hybrid S213 (schwarz)Kleinmetall Starliner mageschneiderte Kofferraumauskleidung Geeignet fr folgendes Fahrzeug: Mercedes E Klasse T Modell Hybrid Typ: S213 Baujahr: 2018 bis 2023 Ladeboden mittig um 13cm erhht NUR passend fr Hybrid! Farbe: schwarz Weitere Eigenschaften: Montagezeit: ca. 20 min Umklappen Rcksitze: Ja, durch Reiverschlsse nderungen am Fahrzeug: Nein Montageart: Befestigung mit Klettverschlssen und Druckverschlssen Mageschneiderte Kofferraumwanne
Kleinmetall Starliner maßgeschneiderte Kofferraumauskleidung
Geeignet für folgendes Fahrzeug:
- Mercedes E-Klasse T-Modell Hybrid Typ: S213
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Baujahr: 2018 bis 2023
- Ladeboden mittig um 13cm erhöht
- NUR passend für Hybrid!
- Farbe: schwarz
Weitere Eigenschaften:
- Montagezeit: ca. 20 min
- Umklappen Rücksitze: Ja, durch Reißverschlüsse
- Änderungen am Fahrzeug: Nein
- Montageart: Befestigung mit Klettverschlüssen und Druckverschlüssen
- Maßgeschneiderte Kofferraumwanne / Kofferraumauskleidung für Ihr Fahrzeug
- Flammhemmende, flexible und strapazierfähige PVC-Folie; wasserfest, leicht zu reinigen
- Schutz vor Schmutz, Tierhaaren und Feuchtigkeit (Wasser, Öl und vielen Chemikalien)
- Ideal für den Transport von verschmutzten Gegenständen aller Art und unentbehrlich für Hobby und Handwerk
- Schützt den Kofferraum von den Kopfstützen bis zur Ladekante inkl. der Seitenwände
- Optional erhältlich: Stoßstangenschutz mit Klett-Befestigung
Bitte beachten!
- Die angezeigten Bilder zeigen ggfls. andere Fahrzeugmodelle! Sie kaufen die Auskleidung für den oben angegeben Fahrzeugtyp!
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4.4 ★★★★★
Based on 20 reviews
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Product Reviews
★★★★★ 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.
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Reviewed in the United States on January 16, 2026
★★★★★ 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.
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Reviewed in the United States on August 12, 2024
★★★★★ 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
★★★★★ 5
Amazing book
Format: Paperback
Excelent product
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Reviewed in the United States on November 4, 2025
★★★★★ 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