SKU: 36111948477

PUIG 20471V Racingscheibe passend fuer KAWASAKI Z1000SX Grün

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PUIG 20471V Racingscheibe passend fuer KAWASAKI Z1000SX GrünPUIG 20471V Racingscheibe passend fuer KAWASAKI Z1000SX 2011 Geben Sie Ihren Motorrad den besonderen Charakter, den Sie durch die Racing Windschutzscheibe von Puig erhalten knnen. Hergestellt aus 3 mm starkem, schlagfestem Acryl, einem widerstandsfhigen und langlebigem Material. Abgerundet auf> 2 mm (gem den TV Bestimmungen). Dank seiner doppelten Hhe wird der Luftstrom auf den Oberkrper und Kopf stark verringert. Diese Windschutzscheibe ist je nach

PUIG 20471V Racingscheibe passend fuer KAWASAKI Z1000SX 2011

Geben Sie Ihren Motorrad den besonderen Charakter, den Sie durch die Racing Windschutzscheibe von Puig erhalten können. Hergestellt aus 3 mm starkem, schlagfestem Acryl, einem widerstandsfähigen und langlebigem Material. Abgerundet auf> 2 mm (gemäß den TÜV-Bestimmungen). Dank seiner doppelten Höhe wird der Luftstrom auf den Oberkörper und Kopf stark verringert. Diese Windschutzscheibe ist je nach Modell in zwei Varianten erhältlich: Z-Racing und R-Racer. Das Design der Z-Racing-Scheibe wurde im Windkanal getestet. Der aerodynamische Koeffizient und der Schutz vor Windböen, wurden gegenüber dem Originalmodell um 12,7% (aufrechte Position) und in der Rennposition um 61% verbessert. Die R-Racer-Scheiben wurde nicht nur im Windkanal untersucht, sondern auch gemeinsam mit Rennteams der WSBK World Championship und Endurance entwickelt, um ein perfektes Gleichgewicht zwischen Schutz und Aerodynamik zu erreichen. Die Montage des Produkts erfordert keine vorherigen Anpassungen an das Motorrad und wird mit den umfassenden, aerodynamischen Studienergebnissen geliefert. Überprüfen Sie, ob das Referenz von der deutschen KBA homologiert wurde und ob es bereits in der Homologation im Abschnitt DOKUMENTE aufgenommen ist. Bitte prüfen Sie die ABE sorgfältig, um sicherzustellen, dass dieses Teil für Ihr Motorrad geeignet ist.

Messungen (Höhe x Breite): 480 X 420 MM

passend für:

KAWASAKI Z1000SX 2011
KAWASAKI Z1000SX 2012
KAWASAKI Z1000SX 2013
KAWASAKI Z1000SX 2014
KAWASAKI Z1000SX 2015
KAWASAKI Z1000SX 2016
KAWASAKI Z1000SX 2017
KAWASAKI Z1000SX 2018
KAWASAKI Z1000SX 2019
KAWASAKI Z1000SX TOURER 2011
KAWASAKI Z1000SX TOURER 2012
KAWASAKI Z1000SX TOURER 2013
KAWASAKI Z1000SX TOURER 2014
KAWASAKI Z1000SX TOURER 2015
KAWASAKI Z1000SX TOURER 2016
KAWASAKI Z1000SX TOURER 2017
KAWASAKI Z1000SX TOURER 2018
KAWASAKI Z1000SX TOURER 2019
KAWASAKI NINJA 1000 SX 2020
KAWASAKI NINJA 1000 SX 2021
KAWASAKI NINJA 1000 SX 2022
KAWASAKI NINJA 1000 SX 2023
KAWASAKI NINJA 1000 SX 2024
KAWASAKI NINJA 1100 SX 2025
KAWASAKI NINJA 1100 SX SE 2025
KAWASAKI NINJA 1100 SX 2026
KAWASAKI NINJA 1100 SX SE 2026

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SKU: 36111948477

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4.9 ★★★★★
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CL
Port Orchard, 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.
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Reviewed in the United States on November 14, 2025
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Amazon Customer
Massapequa, 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.
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Reviewed in the United States on September 2, 2024
M
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MrGee
Phoenix, US
★★★★★ 5
An enjoyable, and seriously excellent, path to understanding Deep Learning...
Format: Paperback
Deep Learning is changing our world. If you want to understand more, this is a great place to start. Andrew Glassner is a talented explainer - I took his short course on Deep Learning and learned so much, but also came away impressed at how well he can make complex material so clear and engaging. And this book is jammed packed with insights, visuals, and clear explanations. The author has a playful, sometimes quirky style that shines through, which gives this tour a lot of personality as well as information. Very enjoyable reading - I felt like he captured all that was good about his course (and then some) and bottled it up in this book. There is a lot more material here than in that course, and it is well laid-out and organized so that it is easy to roam around and come back to review the pieces that matter to you. Even if you plan to go to on to be a world-class Deep Learning engineer or mathematician, you have to start by understanding the concepts. And this book does a great job of presenting all the core ideas in a way that makes them clear and memorable.
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Reviewed in the United States on August 5, 2021
R
Verified Purchase
R. Cote
Los Angeles, US
★★★★★ 5
Before GPT can chat, it has to learn.
Format: Paperback
One of the most comprehensive guides to AI and deep learning available. All concepts covered clearly and concisely with illustrations. Complex concepts are broken down into understandable terms. Even though ML and AI require some complex math, you won’t need it to get idea of what’s going on inside the computer’s “brain”. I use this as a reference when teaching AI concepts and preparing presentations. I highly recommend it
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Reviewed in the United States on April 5, 2025
R
Verified Purchase
Rafael Azevedo Souza Costa
Waukegan, US
★★★★★ 5
Great examples and practical explanations
Format: Paperback
Excellent book. Highly recommend
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 19, 2025

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