1987-1992 Suzuki DT175 L/XL EFI Fuel Pump 15100-92E02 15100-92E01
SKU: 797990530

1987-1992 Suzuki DT175 L/XL EFI Fuel Pump 15100-92E02 15100-92E01

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Description

1987-1992 Suzuki DT175 L/XL EFI Fuel Pump 15100-92E02 15100-92E01EFI Fuel Pump for Suzuki DT150 DT175 DT200 DT225 1987 2003 Replaces 15100 92E02, 15100 92E01 Features: Meet or exceed OEM performance and durability. Polished corrosion resistant case to help minimize seizing during non operation. Drop in replacement design. performance and durability. Compatible with modern ethanol infused pump gasoline. Money saving, factory direct fuel pump typically priced less than OEM counterparts. Includes inline electric fuel

EFI Fuel Pump for Suzuki DT150 DT175 DT200 DT225 1987-2003 Replaces 15100-92E02, 15100-92E01

Features:
Meet or exceed OEM performance and durability.
Polished corrosion-resistant case to help minimize seizing during non-operation.
Drop in replacement design.
performance and durability.
Compatible with modern ethanol-infused pump gasoline.
Money-saving, factory direct fuel pump typically priced less than OEM counterparts.
Includes inline electric fuel pump, outlet elbows, crush washers, electrical boots and terminals.
Professional installation will be highly recommanded,instruction NOT included.

Specifications:
Condition: Aftermarket 100% Brand New
Material: Metal
Type: Fuel Pump
Gas Type: ?Gasoline

Replacement Part Number:
15100-92E02
15100-92E01

Fits Make/Model/Year:
Fit for Suzuki DT150 L/XL 1987-2003
Fit for Suzuki DT150 SL 1999-2000
Fit for Suzuki DT150 (G)L/XL 1990-1997
Fit for Suzuki DT175 L/XL 1987-1992
Fit for Suzuki DT200 L/UL 1998-2000
Fit for Suzuki DT200 L/XL 1988-1998
Fit for Suzuki DT225 L/XL 1992-2003

(Compatibility Chart is for Reference ONLY!!!)
(Please Compare with Your faulty unit and the image we provided to Decide Fitment)

Package includes:
1x Fuel Pump Assy

(Comes exactly as pictured.)

Note:
The product on offer is an accessory or spare part and thus is not an original product of the vehicle manufacturer.
The name of the vehicle manufacturer is stated only as an indication of the determination of the product being offered as an accessory or spare part, to clarify, for which vehicle the product on offer fits.

Warranty:
Returns: Customers have the right to apply for a return within 60 days after the receipt of the product
24-Hour Expert Online: Solve your installation and product problems

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SKU: 797990530

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4.5 ★★★★★
Based on 1728 reviews
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Product Reviews
O
Om S
Phoenix, US
★★★★★ 4
Title: Really Good Book for Learning LLMs
Format: Paperback, Format: Paperback
I picked up this book after struggling with LLM implementation at work. Ken Huang explains things clearly without too much technical jargon. The book covers everything from data preparation to building AI agents. I especially liked the chapters on RAG and prompting techniques - they helped me improve my current projects. The code examples actually work, which is nice. Some parts are pretty advanced, so you need basic Python knowledge. I had to read a few chapters twice to fully get it. The fairness and bias detection section was eye-opening. Good practical advice throughout. Not just theory - real solutions you can use. Worth the money if you're serious about LLM development. Recommended for anyone building AI systems professionally.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on July 25, 2025
J
Jiewen Wang
Fort Morgan, US
★★★★★ 5
a comprehensive guide at the intersection of generative AI and cybersecurity
Format: Kindle
This book blends deep theoretical foundations with practical frameworks and forward-looking strategies. From adversarial risk models to actionable guidance using OWASP Top 10 for LLMs and the NIST AI RMF, it offers both technical depth and operational clarity. What makes it stand out is its balance of academic rigor and real-world CISO insights, providing a holistic perspective on securing GenAI systems. While it leans enterprise-focused, the content remains accessible to security engineers, risk managers, and policy leaders alike. Generative AI Security is a timely and essential read for anyone working to deploy GenAI responsibly—building systems with both power and integrity in today’s fast-evolving threat landscape.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on July 2, 2025
N
Nader
West Palm Beach, 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
Boise, 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
Massapequa, 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

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