SKU: 14818944405

BikeMaster TruGel Battery - MG12-BS

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Description

BikeMaster TruGel Battery - MG12-BSThe TruGel Battery by BikeMaster is a gel electrolyte powersports battery with a life span twice that of a wet battery. Able to resist vibration and impacts that damage regular wet batteries, it can be installed on your bike at any angle. This Part Fits: Year Make Model Submodel 2017 2019 Aprilia Dorsoduro 900 Base 2001 2004 Aprilia RST1000 Futura Base 2005 2009 Aprilia RSV 1000 R Base 2004 2009 Aprilia RSV 1000 R Factory Base 2001 2004 Aprilia RSV

The TruGel Battery by BikeMaster® is a gel electrolyte powersports battery with a life span twice that of a wet battery. Able to resist vibration and impacts that damage regular wet batteries, it can be installed on your bike at any angle.

This Part Fits:

Year Make Model Submodel
2017-2019 Aprilia Dorsoduro 900 Base
2001-2004 Aprilia RST1000 Futura Base
2005-2009 Aprilia RSV 1000 R Base
2004-2009 Aprilia RSV 1000 R Factory Base
2001-2004 Aprilia RSV Mille Base
2017-2019 Aprilia Shiver 900 Base
2009-2011 Aprilia Sportcity 250 Base
2002-2005 Aprilia Tuono 1000 Base
2003-2011 Aprilia Tuono 1000 R Base
2004-2010 Aprilia Tuono 1000 R Factory Base
2017,2020,2022 Arctic Cat Alterra 300 Base
2006-2008 Arctic Cat DVX 250 Base
2009-2015 Arctic Cat DVX 300 Base
1998-2000 Bimota SB8R Base
2022-2023 BMW F750GS Base
2022-2023 BMW F850GS Base
2022-2023 BMW F850GS Adventure Base
2022-2023 BMW F900R Base
2022-2023 BMW F900XR Base
2007-2020,2022-2023 Can-Am DS 250 Base
1986-1987 Honda ATC125M Base
1985-1987 Honda ATC250ES Big Red Base
1985-1987 Honda ATC250SX Base
1994-1995 Honda CB1000 Base
1997-2000 Honda CBR1100XX Super Blackbird Base
1985 Honda FL350R Odyssey Base
1989-1990,1994-1998 Honda PC800 Pacific Coast Base
2005-2006 Honda PS250 Big Ruckus Base
1986-1988 Honda TRX200SX Base
1985-1987 Honda TRX250 Base
2002-2009,2011-2014,2016-2020,2022 Honda TRX250TE FourTrax Recon ES Base
1997-2009,2011-2014,2016-2020,2022 Honda TRX250TM FourTrax Recon Base
1994-2003 Honda VF750C Magna Base
1995-1996 Honda VF750CD Magna Deluxe Base
2022-2023 Kawasaki EJ800 W800 Base
2009-2010 Kawasaki ER-6N Base
2006-2011 Kawasaki EX650 Ninja 650R Base
2008-2020 Kawasaki KLE650 Versys Base
2022 Kawasaki KLE650 Versys ABS Base
2022 Kawasaki KLE650 Versys ABS LT Base
2013-2018,2020-2025 Kawasaki KVF300 Brute Force Base
2004-2005 Kawasaki VN800A Vulcan 800 Base
2004-2005 Kawasaki VN800B Vulcan 800 Classic Base
2004-2006 Kawasaki VN800E Vulcan 800 Drifter Base
2006-2024 Kawasaki VN900B Vulcan 900 Classic Base
2007-2024 Kawasaki VN900C Vulcan 900 Custom Base
2006-2024 Kawasaki VN900D Vulcan 900 Classic LT Base
1991-1993 Kawasaki ZR750C Zephyr Base
1993-2002 Kawasaki ZX600 Ninja ZX-6 Base
1995-1997 Kawasaki ZX600 Ninja ZX-6R Base
1996-2003 Kawasaki ZX750 Ninja ZX-7R Base
1994-1997 Kawasaki ZX900 Ninja ZX-9R Base
2003-2004 Kawasaki ZZR 600 Base
2009-2011 KYMCO People S 250 Base
2005-2020,2022-2023 Polaris Phoenix 200 Base
2014 Polaris RZR 170 Base
2022 Polaris RZR 200 EFI Base
2006-2007 Polaris Sawtooth Base
2005-2009,2013,2015-2020 Suzuki C50 Boulevard Base
2005-2009,2011-2020 Suzuki C50T Boulevard Base
2004-2011 Suzuki DL650 V-Strom Base
2022 Suzuki DL650A V-Strom 650 ABS Base
2022 Suzuki DL650A V-Strom 650XT Base
2022 Suzuki DL650A V-Strom 650XT Adventure Base
1994-1995 Suzuki DR650S Base
1997-2005 Suzuki GSF1200S Bandit Base
2001-2004 Suzuki GSX-R1000 Base
1993-1998 Suzuki GSX-R1100 Base
1992-1993 Suzuki GSX-R600 Base
1993 Suzuki GSX-R750 Base
2008 Suzuki GSX1300BK B-King Base
2008-2020 Suzuki GSX1300R Hayabusa Base
2002-2009,2012-2013 Suzuki LT-F250 Ozark Base
1988-1993 Suzuki LT230E QuadRunner Base
2013-2019 Suzuki M50 Boulevard Base
1997-2001 Suzuki TL1000S Base
2001-2004 Suzuki VL800 Intruder Volusia Base
1997-2004 Suzuki VZ800 Marauder Base
2009-2011 Triumph Bonneville Base
2009-2013 Triumph Bonneville SE Base
2009-2015,2017-2019 Triumph Bonneville T100 Base
2006-2016 Triumph Scrambler Base
2005-2012 Triumph Speed Triple Base
2005-2010 Triumph Sprint ST Base
2000-2003 Triumph TT600 Base
1992-1993 Yamaha TDM850 Base
2012-2013 Yamaha YFM300 Grizzly Automatic Base
1997-2007 Yamaha YZF600R Base
1994-1998 Yamaha YZF750R Base
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SKU: 14818944405

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4.4 ★★★★★
Based on 24 reviews
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Product Reviews
N
Nader
Grantham, US
★★★★★ 1
Light on substance and heavy on flaws
Format: Paperback
The book has a great list of topics, but fails to provide much substance any of them. Most of the provided code is just comments that avoid the actual crux of the issues being discussed. (e.g. #implement the logic to validate XYZ - while the whole point of this chapter is teach how the heck we validate XYZ!) Some parts are plain wrong, for example the part on Graph based RAG is fundamentally flawed as it assumes the text embedding and the graph embedding are in the same latent space. (This is one of many more examples). Seems like the book was rushed, and the author has limited hands on experience (if any). At least we know based on the amount of flaws that it was not written by an LLM
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on December 31, 2025
N
noam barkay
Omaha, 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
Battle Creek, 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
Fort Morgan, 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
Omaha, 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

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