SKU: 11116259452

PUIG 21023P Lenkerenden Sport passend fuer YAMAHA XJR1300 Silber

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Description

PUIG 21023P Lenkerenden Sport passend fuer YAMAHA XJR1300 SilberPUIG 21023P Lenkerenden Sport passend fuer YAMAHA XJR1300 1999 Aus einem Aluminiumblock gefrst und in sieben verschiedenen Farben anodisiert. Sein Design verbindet die Einfachheit der Linien und den Minimalismus des Renn Charakters. Dieses Gegengewicht ist ein 40mm langes Modell. Es gibt ein Universalmodell und spezifische Modelle fr die meisten Motorrder. M16 150 passend fr: YAMAHA XJR1300 1999 YAMAHA TDM900 2003 YAMAHA TZR50 2003 YAMAHA TZR50 2004

PUIG 21023P Lenkerenden Sport passend fuer YAMAHA XJR1300 1999

Aus einem Aluminiumblock gefräst und in sieben verschiedenen Farben anodisiert. Sein Design verbindet die Einfachheit der Linien und den Minimalismus des Renn Charakters. Dieses Gegengewicht ist ein 40mm langes Modell. Es gibt ein Universalmodell und spezifische Modelle für die meisten Motorräder.

M16/150

passend für:

YAMAHA XJR1300 1999
YAMAHA TDM900 2003
YAMAHA TZR50 2003
YAMAHA TZR50 2004
YAMAHA YZF 600 R THUNDERCAT 1996
YAMAHA YZF 600 R THUNDERCAT 1997
YAMAHA YZF 600 R THUNDERCAT 1998
YAMAHA YZF 600 R THUNDERCAT 1999
YAMAHA YZF 600 R THUNDERCAT 2000
YAMAHA YZF 600 R THUNDERCAT 2001
YAMAHA YZF 600 R THUNDERCAT 2002
YAMAHA YZF 1000 R THUNDERACE 1997
YAMAHA YZF 1000 R THUNDERACE 1998
YAMAHA YZF 1000 R THUNDERACE 1999
YAMAHA YZF 1000 R THUNDERACE 2000
YAMAHA YZF 1000 R THUNDERACE 2001
YAMAHA FZS1000 FAZER 2002
YAMAHA FZS1000 FAZER 2003
YAMAHA FZS1000 FAZER 2004
YAMAHA FZS1000 FAZER 2001
YAMAHA TDM 850 1996
YAMAHA TDM 850 1997
YAMAHA TDM 850 1998
YAMAHA TDM 850 1999
YAMAHA TDM 850 2000
YAMAHA TDM 850 2001
YAMAHA TDM900 2004
YAMAHA TDM900 2005
YAMAHA FZS1000 FAZER 2005
YAMAHA XJR1200 1997
YAMAHA XJR1200 1998
YAMAHA XJR1300 2000
YAMAHA XJR1300 2001
YAMAHA XJR1300 2002
YAMAHA XJR1300 2003
YAMAHA XJR1300 2004
YAMAHA FZ1 FAZER 2006
YAMAHA FZ6 2005
YAMAHA FZ6 2006
YAMAHA TDM900 2006
YAMAHA TZR50 2005
YAMAHA TZR50 2006
YAMAHA XJR1300 2005
YAMAHA XJR1300 2006
YAMAHA FZ1 FAZER 2007
YAMAHA XJR1300 2007
YAMAHA TDM900 2007
YAMAHA TZR50 2007
YAMAHA FZ6 2007
YAMAHA YZF-R125 2008
YAMAHA FZ1 FAZER 2008
YAMAHA TDM900 2002
YAMAHA TDM900 2008
YAMAHA XJR1300 2008
YAMAHA FZ6 2004
YAMAHA FZ6 2008
YAMAHA FZ1 FAZER 2009
YAMAHA TDM900 2009
YAMAHA XJR1300 2009
YAMAHA YZF 1000 R THUNDERACE 1996
YAMAHA YZF-R125 2009
YAMAHA XJ6 2009
YAMAHA XJ6 DIVERSION 2009
YAMAHA FZ1 FAZER 2010
YAMAHA XJ6 2010
YAMAHA XJ6 DIVERSION 2010
YAMAHA XJ6 DIVERSION F 2010
YAMAHA TDM900 2010
YAMAHA YZF-R125 2010
YAMAHA XJR1300 2010
YAMAHA FZ1 FAZER 2011
YAMAHA TDM900 2011
YAMAHA XJ6 2011
YAMAHA XJ6 DIVERSION F 2011
YAMAHA YZF-R125 2011
YAMAHA TZR50 2008
YAMAHA TZR50 2009
YAMAHA TZR50 2010
YAMAHA TZR50 2011
YAMAHA XJ6 DIVERSION 2011
YAMAHA XJR1300 2011
YAMAHA FZ1 FAZER 2012
YAMAHA XJ6 2012
YAMAHA XJ6 DIVERSION 2012
YAMAHA XJ6 DIVERSION F 2012
YAMAHA XJR1300 2012
YAMAHA TDM900 2012
YAMAHA YZF-R125 2012
YAMAHA TZR50 2012
YAMAHA T-MAX 500 2008
YAMAHA T-MAX 500 2009
YAMAHA T-MAX 500 2010
YAMAHA T-MAX 500 2011
YAMAHA FZ1 FAZER 2013
YAMAHA TDM900 2013
YAMAHA TZR50 2013
YAMAHA XJ6 2013
YAMAHA XJ6 DIVERSION 2013
YAMAHA XJ6 DIVERSION F 2013
YAMAHA YZF-R125 2013
YAMAHA XJR1300 2013
YAMAHA YZF 1000 R THUNDERACE 2002
YAMAHA XJR1200 1994
YAMAHA MT-09 2014
YAMAHA MT-07 2014
YAMAHA FZ1 FAZER 2014
YAMAHA TZR50 2014
YAMAHA XJ6 DIVERSION F 2014
YAMAHA XJ6 DIVERSION 2014
YAMAHA XJ6 2014
YAMAHA MT-09 2013
YAMAHA T-MAX 530 2012
YAMAHA T-MAX 530 2013
YAMAHA T-MAX 530 2014
YAMAHA X-MAX 250 2014
YAMAHA XJR1200 1995
YAMAHA XJR1200 1996
YAMAHA YZF 1000 R THUNDERACE 2003
YAMAHA MT-125 2015
YAMAHA T-MAX 530 2015
YAMAHA TZR50 2015
YAMAHA FZ1 FAZER 2015
YAMAHA MT-07 2015
YAMAHA MT-09 2015
YAMAHA XJ6 2015
YAMAHA XJ6 DIVERSION 2015
YAMAHA XJ6 DIVERSION F 2015
YAMAHA MT-07 2016
YAMAHA MT-10 2016
YAMAHA XSR900 2016
YAMAHA MT-09 2016
YAMAHA MT-125 2016
YAMAHA XJ6 2016
YAMAHA XJ6 DIVERSION 2016
YAMAHA XJ6 DIVERSION F 2016
YAMAHA XSR700 2016
YAMAHA T-MAX 530 2016
YAMAHA TZR50 2016
YAMAHA MT-125 2017
YAMAHA MT-07 2017
YAMAHA MT-09 2017
YAMAHA XSR700 2017
YAMAHA XSR900 2017
YAMAHA T-MAX 530 2017
YAMAHA T-MAX 530 DX 2017
YAMAHA T-MAX 530 SX 2017
YAMAHA MT-10 2017
YAMAHA MT-10 SP 2017
YAMAHA XJR1300 2014
YAMAHA XJR1300 2015
YAMAHA XJR1300 2016
YAMAHA MT-125 2014
YAMAHA MT-10 SP 2018
YAMAHA MT-10 2018
YAMAHA XSR700 2018
YAMAHA MT-09 2018
YAMAHA XSR900 2018
YAMAHA MT-125 2018
YAMAHA MT-09 SP 2018
YAMAHA T-MAX 530 2018
YAMAHA T-MAX 530 DX 2018
YAMAHA T-MAX 530 SX 2018
YAMAHA MT-07 2019
YAMAHA XSR700 XTRIBUTE 2019
YAMAHA MT-10 2019
YAMAHA MT-10 SP 2019
YAMAHA MT-125 2019
YAMAHA MT-09 2019
YAMAHA MT-09 SP 2019
YAMAHA XSR700 2019
YAMAHA XSR900 2019
YAMAHA YZF-R125 2019
YAMAHA YZF-R125 2020
YAMAHA MT-10 2020
YAMAHA MT-10 SP 2020
YAMAHA MT-09 2020
YAMAHA MT-09 SP 2020
YAMAHA MT-07 2020
YAMAHA XSR700 2020
YAMAHA XSR700 XTRIBUTE 2020
YAMAHA XSR900 2020
YAMAHA MT-125 2020
YAMAHA YZF-R125 2021
YAMAHA MT-10 SP 2021
YAMAHA MT-125 2021
YAMAHA XSR900 2021
YAMAHA XSR700 2021
YAMAHA MT-125 2022
YAMAHA YZF-R125 2022
YAMAHA XSR700 2022
YAMAHA MT-10 2022
YAMAHA MT-10 SP 2022
YAMAHA MT-10 SP 2023
YAMAHA MT-10 2023
YAMAHA MT-125 2023
YAMAHA NIKEN 2023
YAMAHA NIKEN GT 2023
YAMAHA XSR700 2023
YAMAHA YZF-R125 2023
YAMAHA MT-07 ABS 2014
YAMAHA MT-07 ABS 2015
YAMAHA MT-07 ABS 2016
YAMAHA MT-07 MOTO CAGE 2014
YAMAHA MT-07 MOTO CAGE 2015
YAMAHA MT-07 MOTO CAGE 2016
YAMAHA MT-07 MOTO CAGE 2017
YAMAHA MT-09 STREET RALLY 2013
YAMAHA MT-09 STREET RALLY 2014
YAMAHA MT-09 STREET RALLY 2015
YAMAHA MT-09 STREET RALLY 2016
YAMAHA MT-09 SPORT TRACKER 2013
YAMAHA MT-09 SPORT TRACKER 2014
YAMAHA MT-09 SPORT TRACKER 2015
YAMAHA MT-09 SPORT TRACKER 2016
YAMAHA XJ6 SP 2009
YAMAHA XJ6 SP 2010
YAMAHA XJ6 SP 2011
YAMAHA XJ6 SP 2012
YAMAHA XJ6 SP 2013
YAMAHA XJ6 SP 2014
YAMAHA XJ6 SP 2015
YAMAHA XJ6 SP 2016
YAMAHA XJR 1300 SP 1999
YAMAHA XJR 1300 SP 2000
YAMAHA XJR 1300 SP 2001
YAMAHA TDM900 2014
YAMAHA TZR50 2017
YAMAHA TZR50 2018
YAMAHA TZR50 2019
YAMAHA TZR50 2020
YAMAHA TZR50 2021
YAMAHA TZR50 2022
YAMAHA TZR50 2023
YAMAHA T-MAX 500 2012
YAMAHA MT-10 2024
YAMAHA MT-10 SP 2024
YAMAHA MT-125 2024
YAMAHA NIKEN GT 2024
YAMAHA XSR700 2024
YAMAHA YZF-R125 2024
YAMAHA MT-10 2025
YAMAHA MT-10 SP 2025
YAMAHA MT-125 2025
YAMAHA NIKEN GT 2025
YAMAHA XSR700 2025
YAMAHA YZF-R125 2025
YAMAHA X-MAX 125 2010
YAMAHA X-MAX 125 2011
YAMAHA X-MAX 125 2012
YAMAHA X-MAX 125 2013
YAMAHA X-MAX 125 2014
YAMAHA X-MAX 125 2015
YAMAHA X-MAX 125 2016
YAMAHA X-MAX 125 2017
YAMAHA X-MAX 125 2018
YAMAHA X-MAX 125 2019
YAMAHA X-MAX 125 2020
YAMAHA X-MAX 125 2021
YAMAHA X-MAX 125 2022
YAMAHA X-MAX 250 2010
YAMAHA X-MAX 250 2011
YAMAHA X-MAX 250 2012
YAMAHA X-MAX 250 2013
YAMAHA X-MAX 250 2015
YAMAHA X-MAX 250 2016
YAMAHA X-MAX 400 2013
YAMAHA X-MAX 400 2014
YAMAHA X-MAX 400 2015
YAMAHA X-MAX 400 2016
YAMAHA X-MAX 400 2017
YAMAHA YP 125 R X-MAX ABS 2014
YAMAHA YP 125 R X-MAX ABS 2015
YAMAHA YP 125 R X-MAX ABS 2016
YAMAHA YP 250 R X-MAX ABS 2014
YAMAHA YP 250 R X-MAX ABS 2015
YAMAHA YP 250 R X-MAX ABS 2016
YAMAHA MT-10 2026
YAMAHA MT-10 SP 2026
YAMAHA MT-125 2026
YAMAHA NIKEN GT 2026
YAMAHA XSR700 2026
YAMAHA YZF-R125 2026
YAMAHA MT-07 2018
YAMAHA T-MAX 530 DX 2019
YAMAHA T-MAX 530 SX 2019
YAMAHA T-MAX 530 2019
YAMAHA T-MAX 560 TECH MAX 2020
YAMAHA T-MAX 560 2020
YAMAHA T-MAX 560 2021
YAMAHA T-MAX 560 TECH MAX 2021
YAMAHA MT-07 2021
YAMAHA MT-07 2022
YAMAHA MT-07 2023
YAMAHA MT-07 2024
YAMAHA MT-07 PURE 2023
YAMAHA MT-07 PURE 2024

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SKU: 11116259452

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N
noam barkay
Birmingham, 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
Louisville, 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
Omaha, 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
Pawtucket, 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
Cuba, 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

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