SKU: 24891119814

2000-2011 Peugeot 206/206SD 1.4L 1.6L 2.0L Valve Body AL4 DPO QMP-L00105

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Description

2000-2011 Peugeot 206/206SD 1.4L 1.6L 2.0L Valve Body AL4 DPO QMP-L00105AL4 DPO Valve Body Fit For Peugeot Citroen Renault 00 11 Beringo C2 C3 C4 C8 C5 DC Feature: 1: According to the original factory specifications,perfect match for the original car. 2: Own different test machines to design exact accurate parameter for our products. All items were tested for performance. 3: Made by high quality material, lightweight, anti rust, colorfast and durable. 4: Aftermarket product with premium quality. 5: Stable performance,

AL4 DPO Valve Body Fit For Peugeot Citroen Renault 00-11 Beringo C2 C3 C4 C8 C5 DC

Feature:
1: According to the original factory specifications,perfect match for the original car.
2: Own different test machines to design exact accurate parameter for our products.All items were tested for performance.
3: Made by high quality material, lightweight, anti-rust, colorfast and durable.
4: Aftermarket product with premium quality.
5: Stable performance, high reliability,suitable for replacing your broken one.

Specifics:
Condition: Remanufactured
Material: Metal
Manufacturer Part Number: AL4, DPO
Interchange Part Number: AL4 DPO
Other Part Number: QMP-L00105
Type: Valve Body
Fitment Type: Direct Replacement

Fitment:
For Citroen
C3/C3 PICASSO 2008-2011 1.6L 2.0L
C3 01-11 1.4L 1.6L
C2 06-10 1.6L
C4/C4 PICASSO 2004-2011 1.6L 2.0L
C5 2001-2004 2.0L 2.2L 2.9L
C8 2002-2011 2.0L
C-TRIOMPHE 2006-2011 2.0L
BERLINGO 00-02 1.6L 1.8L

For Peugeot
206/206SD 2000-2011 1.4L 1.6L 2.0L
207/207 PASSION 06-11 1.6L
306 2000-2002 1.8L 2.0L
307 2001-2011 1.6L 2.0L
308 2007-2011 1.6L 2.0L
406/406 COUPE 2000-2005 1.7L 1.8L 2.0L
407 2003-2011 2.0L
408 2011-ON 2.0L
807 2002-2010 2.0L

For RENAULTCLIO
2000-2011 1.4L 1.6L 2.0L
ESPACE 2000-2002 2.0L
FLUENCE 2009-2011 1.6L 2.0L
KANGOO/KANGOO LCV 00-11 1.4L 1.5L 1.6L
LAGUNA 2000-2007 1.8L 1.9L 2.0L
LOGAN 07-10 1.6L
MEGANE 2000-2011 1.4L 1.5L 1.6L 1.9L 2.0L
MODUS 04-11 1.6L
SAFRANE 2000-ON 2.0L 2.2L
SCENIC 2000-2011 2.0L
SYMBOL/THALIA 00-11 1.4L 1.6L

For LANCIA
PHEDRA 2002-2005 2.0L

For KIA
206 BESTARI* 06-09 1.4L

For NISSAN
PLATINA 02-10 1.6L

***If you are not sure, please provide vin for us

Package Include:
1 x Valve Body
High Quality, Strictly tested.
(Instruction is not inclued!)

Note:
1.Please check the description or use the year/make/model check finder and replace part numbers to confirm the compatibility before purchasing.
2.Professional installation is recommended.

Installation Video (FOR REFERENCE ONLY):

https://youtu.be/UvzBHz70avs?si=E8ZAlBE7wrZiRGKw
(Please note, the installation video is for reference only and may not be completely accurate. If you're unsure about installation, we recommend consulting a local professional mechanic for assistance.)

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

Shipping Notes
  • Free Standard Shipping on $100+ Orders to the USA.
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Exchange/Return Notes
  • We offer a 30-day return/exchange service after receiving.
  • Final sale items are not eligible for returns or exchanges.
  • To process your return/exchange, please contact us at [email protected]
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SKU: 24891119814

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4.8 ★★★★★
Based on 5 reviews
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Product Reviews
R
Ryan Meyer
Grantham, 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
Charlottesville, 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.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on September 2, 2024
M
Verified Purchase
MrGee
Houston, 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.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on August 5, 2021

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