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MULTICOMP 108-4002 Protective Clothing, Lab Coat, ESD Safe, White, LargeThis is a Protective Clothing, Lab Coat, ESD Safe, White, Large product from MULTICOMP with the model number 108 4002Product details Clothing Style Lab Coat Clothing Colour White Clothing Size Large Clothing Material 65% Polyester, 33% Cotton and 2% Conductive Filament Product Range Other details Brand MULTICOMP Part Number 108 4002 Quantity Each Technical Data Sheet EN Miscellaneous EN All product and company names are trademarks or registered
This is a Protective Clothing, Lab Coat, ESD Safe, White, Large product from MULTICOMP with the model number 108-4002Product details
| Clothing Style | Lab Coat |
| Clothing Colour | White |
| Clothing Size | Large |
| Clothing Material | 65% Polyester, 33% Cotton and 2% Conductive Filament |
| Product Range | - |
Other details
| Brand | MULTICOMP |
| Part Number | 108-4002 |
| Quantity | Each |
| Technical Data Sheet EN | |
| Miscellaneous EN |
All product and company names are trademarks™ or registered® trademarks of their respective holders. Use of them does not imply any affiliation with or endorsement by them. Image is for illustrative purposes only. Please refer to product description.
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4.2 ★★★★★
Based on 270 reviews
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Product Reviews
★★★★★ 2
Just linear
Format: Paperback
I appreciate that it helps to organize the chaos of information, but I just used the template verbatim with my manager and it did not go very well. He said this linear approach does not work anymore with high-level corporate audiences. They want to cut right to the chase and start to dig into the deep details. This layout with simple images, even if you just pull away the map and anchor slides, makes the storytelling too much like a story, not giving enough credit to the speed at which certain audiences can and do process data on a slide. It was an interesting exercise and I still think this linear layout works in some cases. Just not if you are trying to communicate business case or other C-suite type of information.
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Reviewed in the United States on March 4, 2021
★★★★★ 5
Excellent AI security book
Format: Paperback
A necessary book for those who in work in the AI Security field. It is easy to read and easy to follow along with practice labs. The author did a good job incorporating the breadth of AI threats.
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Reviewed in the United States on January 10, 2026
★★★★★ 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