SKU: 10997105620
kinguard fahrradschloss

kinguard fahrradschloss OnGuard RockSolid 8590 Ultra-robustes und leichtes U-Fahrradschloss

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Description

kinguard fahrradschloss OnGuard RockSolid 8590 Ultra-robustes und leichtes U-FahrradschlossDas RockSolid von Onguard bietet das hchste mgliche Sicherheitsniveau und bleibt dabei kompakt und handlich ideal, um dein Fahrrad in der Stadt bei tglichen Fahrten zu schtzen! Maximale Sicherheit Dieses Schloss ist mit 99 100 auf der Sicherheitsskala der OnGuard Schlsser bewertet, einer Referenzmarke im Bereich Fahrradschlsser. Es hat die Zertifizierung Diamond Sold Secure erhalten die hchste Auszeichnung von Sold Secure, die Schlsser zahlreichen

Das RockSolid von Onguard bietet das höchste mögliche Sicherheitsniveau und bleibt dabei kompakt und handlich – ideal, um dein Fahrrad in der Stadt bei täglichen Fahrten zu schützen!

Maximale Sicherheit

Dieses Schloss ist mit 99/100 auf der Sicherheitsskala der OnGuard-Schlösser bewertet, einer Referenzmarke im Bereich Fahrradschlösser. Es hat die Zertifizierung Diamond Sold Secure erhalten – die höchste Auszeichnung von Sold Secure, die Schlösser zahlreichen Tests unterzieht, basierend auf bekannten Diebstahlmethoden der Polizei und Versicherungen. Mit diesem Fahrradschloss hat OnGuard die Formel für maximale Sicherheit gefunden!

Das RockSolid wurde entwickelt, um Winkelschleifern zu widerstehen, einem leistungsstarken und vielseitigen Werkzeug, das viele Schlösser leicht knacken kann. OnGuard hat eine einzigartige Kombination aus ultrarobusten Materialien und einer komplexen Schutzstruktur entwickelt, um diesem Werkzeug standzuhalten. Der gehärtete Stahlbügel mit seiner patentierten Beschichtung widersteht verschiedenen Angriffsmethoden. Er verriegelt beidseitig an vier Punkten für noch mehr Widerstandskraft, und der stoßfeste Zylinder wurde verbessert, um Manipulationsversuchen am Schloss und Bohrangriffen standzuhalten. Zudem wurde das Schloss so gestaltet, dass es keine Hebelpunkte für Aufbruchversuche bietet.

Kurzum: ein zuverlässiges Schloss, um dein Fahrrad in der Stadt abzustellen!

Ein Schloss auf höchstem Niveau, das dennoch leicht und handlich bleibt

Ein Fahrradschloss muss praktisch und handlich sein, damit es sich leicht transportieren, entnehmen und verstauen lässt, ohne dich zu belasten. OnGuard ist es gelungen, höchste Sicherheitsansprüche mit den Bedürfnissen der Radfahrer zu kombinieren. Das RockSolid ist das kleinste und leichteste der Winkelschleifer-resistenten Schlösser. Mit einem Gewicht von 1,4 kg bleibt es zwar ein eher schweres Objekt, doch es ist selten, ein so hohes Maß an Sicherheit in einem so kompakten Schloss zu finden.

Das RockSolid wurde speziell für den täglichen Gebrauch entwickelt. Es ist mit einer Schutzbeschichtung versehen, um dein Fahrrad vor Stößen und Kratzern zu bewahren, und ist an den Seiten verstärkt, um Stürze und Schläge abzufangen. Es ist ergonomisch, leicht zu bedienen und verfügt sogar über ein automatisches Schloss-Schutzsystem: eine kleine mechanische Abdeckung, die sich beim Einführen des Schlüssels öffnet und danach wieder schließt, um das Schloss vor äußeren Einflüssen zu schützen, ohne den Schließvorgang zu behindern. Dieses Schloss wird mit 5 Schlüsseln geliefert – so gehst du kein Risiko mehr ein, ohne Ersatz dazustehen!

Dieses kompakte Schloss kann mit einem Kabelschloss ergänzt werden, um dein zweites Rad zu sichern. Um dein Schloss am Fahrrad zu befestigen, kannst du eine universelle Klett-Halterung verwenden.

Entdecke alle unsere Tipps, um Diebe durch die richtige Art, dein Fahrrad anzuschließen, abzuschrecken:

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SKU: 10997105620

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4.1 ★★★★★
Based on 27 reviews
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Product Reviews
N
noam barkay
San Leandro, US
★★★★★ 5
Excellent book to truly understand LLM design patterns
Format: Paperback
I just finished reviewing Ken Huang's pocket book on LLM Design Patterns, and WOW what an amazing resource! This book is excellent if you want to truly understand how to create and enhance intelligent AI language models, all that in your pocket! Ken makes the difficult things seem surprisingly easy, and that's the real MAGIC. - How to prepare your data for training by making it extremely clean. Developing the brains: the practical aspects of training, optimizing, and maintaining your models. - Learn amazing prompting techniques (such as Chain-of-Thought and Tree-of-Thoughts) to improve your AI's reasoning and problem-solving abilities. Learn everything there is to know about RAGs so that your LLM can incorporate outside expertise. - It also delves into creating "agentic" AI that is capable of action and planning (not only simple plan and execute but also enhanced techniques like ReWoo!) Really, this feels like a useful toolkit, so Ken thank you for that resource Thanks, Idan Habler
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on June 9, 2025
R
Ryan Meyer
Natrona Heights, US
★★★★★ 3
A Broad Overview, But Light on Modern Fine-Tuning
Format: Paperback
I'm currently really interested in fine-tuning LLMs and recently completed my first LoRA-based fine-tuning on a quantized model. I came to this book looking for more detail on fine-tuning. While it touches on the topic, I found the content didn’t quite align with the current state of the field in 2025. Techniques like LoRA, QLoRA, and PEFT weren’t really covered, and the material leaned more toward what I think are older or lower level approaches. That made it harder to connect with what I’m actually working on. That said, when I shifted to other chapters — like the sections on prompt engineering techniques such as Chain of Thought (CoT) and Tree of Thought (ToT) — I found more value. These sections were clearer, and I picked up a few practical insights, like using few-shot examples that walk through the CoT reasoning process. That’s not something I’ve tried before, and I can see how it might help smaller models that struggle with any type of reasoning tasks. Overall, the book feels more like a broad overview of all LLM concepts. For someone exploring many topics across the LLM ecosystem, it offers a wide-ranging introduction. But for readers like me who are actively trying to learn and apply techniques like fine-tuning and quantization, it may leave you wanting up-to-date guidance.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on August 10, 2025
V
Vineeth Sai
West Palm Beach, US
★★★★★ 5
Great foundation read for security!
Format: Paperback
This book is a great read! It builds a strong foundation and I would highly recommend it for builders who are interetsed in building on LLMs and ensuring everything is secure. Security is super important and this book does it justice!
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on June 27, 2025
C
Verified Purchase
CL
West Palm Beach, US
★★★★★ 5
Loved it
Format: Paperback
I’ve easily read dozens of tech books. I liked this one a lot. Sure, there were boring parts, but most of it was engaging, especially on dry subjects. I previously read “How AI Works” and found this more informative and way more enjoyable. I got through the 700 pages in about 5 weeks while also learning about probability and linear algebra from other books and online sources. I’d love to read something more advanced by the author, maybe getting into more modern applications. I feel more comfortable with the subject and feel I am now ready to conquer more advanced texts. I initially picked this up to give me some background before reading “How to Build a LLM (from scratch)”. I’ve ordered an intermediary Deep Learning with Python book as well, but wouldn’t mind a more advanced theory book to accompany these books. I’ll definitely be rereading sections of this book to further familiarize myself with topics like backpropagation. Highly recommend if you’re looking for a gentle, but broad introduction to the topic.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on November 14, 2025
A
Verified Purchase
Amazon Customer
New York, US
★★★★★ 5
A Good Place to Start Learning AI
Format: Paperback
Diving into the world of artificial intelligence can feel like stepping into a vast, uncharted ocean, and if you're looking for a reliable vessel to navigate these waters, this book is an excellent choice. However, I must be candid—this journey is not for the faint-hearted or those hoping to breeze through. The subject of AI, with its complex algorithms and intricate theories, is notoriously challenging. You won't find yourself flipping pages at a rapid pace, as this is not a title designed for speed-reading. Instead, it demands your full attention and a willingness to engage deeply with the material. At the heart of AI lies mathematics—a fundamental pillar that underpins the entire discipline. This book, while comprehensive, offers only a glimpse into the mathematical framework that drives artificial intelligence. But don’t be disheartened by this. Think of it as a solid foundation, a primer that will arm you with the essential concepts needed before you delve deeper into the more advanced mathematical intricacies elsewhere. When you do eventually tackle those more complex equations, you'll find yourself better equipped, with a clearer understanding of the principles at play. I should also mention that I'm no stranger to Andrew's work. Having explored some of his other writings, I can confidently say that he possesses a unique flair for communication. His ability to distill complex ideas into accessible language, without losing the essence of the subject, is truly commendable. Andrew writes with a certain finesse and sophistication that makes even the most daunting topics seem approachable. His style is not just informative, but also engaging, with a touch of elegance that sets his work apart from others in the field. In summary, while the path to mastering AI is undeniably steep, this book serves as an invaluable guide. It’s not just a starting point; it’s a beacon for those who are serious about understanding the intricacies of artificial intelligence. Be prepared to invest time and effort, and in return, you'll gain a solid foothold in a subject that is as fascinating as it is complex.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on September 2, 2024

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