suzuki jimny roof top tent Buy roof rack ExRoof for Suzuki Jimny GJ
SKU: 40748474791
suzuki jimny roof top tent

suzuki jimny roof top tent Buy roof rack ExRoof for Suzuki Jimny GJ

$20.55 $22.83
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Description

suzuki jimny roof top tent Buy roof rack ExRoof for Suzuki Jimny GJAnyone who travels in an off road vehicle or van knows the problem: luggage and equipment pile up inside and at every stop you clear everything from left to right. The space inside is very limited, especially with the Suzuki Jimny. So what could be more practical than moving some of the equipment to the roof? Whether transport boxes, canisters, rescue boards or even a roof tent, you can transport everything safely on the ExRoof roof rack for the Jimny

Anyone who travels in an off-road vehicle or van knows the problem: luggage and equipment pile up inside and at every stop you clear everything from left to right. The space inside is very limited, especially with the Suzuki Jimny. So what could be more practical than moving some of the equipment to the roof? Whether transport boxes, canisters, rescue boards or even a roof tent, you can transport everything safely on the ExRoof roof rack for the Jimny GJ.

Light and stable

The ExRoof is made of high-quality powder-coated aluminum 6063 and weighs just 21.5 kg, making it a real lightweight. But don't let its lightness fool you. Despite its slim shape, the roof rack can dynamically carry up to 100 kg and statically even up to 300 kg.

Full of space

With a size of 1698 mm x 1350 mm x 49 mm, the ExRoof roof rack for the Jimny offers enough space to reliably store your equipment. With the all-round profile rail, you can attach a variety of attachments using sliding blocks, which are available as accessories. This means you can adapt the roof rack perfectly to your needs.

Extensive accessories

As a further extra for the ExRoof roof rack, there are lashing eyes to secure your luggage. They are also easy to attach to the ExRoof roof rack. And for all roof tent fans, there are roof tent quick-release fasteners for the ExRoof. This allows you to assemble your roof tent quickly and easily. You can also secure the quick-release fasteners with locks to protect your roof tent from theft. Please note, these accessories are not included with the roof rack and must be ordered separately.

Technical data:

  • Material: aluminum 6063
  • Weight: 21.5 kg
  • Surface: powder coating
  • Size: 1698 mm x 1350 mm x 49 mm

Scope of delivery:

  • Basic support
  • Roof rack feet
  • Fastening material and installation instructions

Hints

Please note that the dynamic load capacity of the ExRoof roof rack does not count as approval from the manufacturer. This means that you must not exceed the maximum load capacity specified by the manufacturer. The static load of the roof rack defines the capacity it can carry when stationary. With regard to the dynamic load, you must note that this is only intended for use on paved roads. To ensure optimal performance and safety, you should always distribute the load evenly and over the entire surface of the roof rack.

Shipping Notes
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SKU: 40748474791

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4.8 ★★★★★
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William P Ross
Draper, US
★★★★★ 5
Comprehensive Look At An Incredibly Complex Topic
Format: Hardcover
Deep Learning is an advanced book with great explanations and details. There is a heavy math focus with the book's beginning chapters detailing the necessary linear algebra and probability that one will need to understand deep learning. I liked that the author's chose to cover only the parts of these subjects which are relevant to deep learning. There are many interesting philosophical sections in the book as well. Just about when I was feeling overwhelmed with the complexity of the mathematics the authors take a step back and cover the foundations of deep learning such as borrowing concepts from human learning. There was an interesting dicussion about the early studies done on the vision of cat's and monkey's in the 1970s. The text covers the entire history of deep learning and the bibliography is hundreds of sources. It is clear this is the most comprehensive text available about deep learning. For anybody interested in this topic this book is a mandatory read. There are sections about machine learning as well, which makes sense because deep learning is a subset of machine learning. These sections focused on the machine learning concepts which are most relevant to deep learning. The book was well organized and divided into three parts which cover mathematics related to deep learning, typical deep learning techniques, and then more experiment learning techniques. Often the author's state when a technique works well or when it does not, and which types of data works best for the technique. Just a warning, the math in this book is highly complex. It requires a lot of work to go through this book, but the effort will be well rewarded.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on March 15, 2017
A
Verified Purchase
Adam
Whiting, US
★★★★★ 4
Too Dry.
Format: Hardcover
This was a required textbook for my class in college. I think it was too dry. The book titled Deep Learning: From Curiosity To Mastery is much more approachable.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 22, 2026
A
Verified Purchase
Amazon Customer
Los Angeles, US
★★★★★ 5
Comprehensive! The Bible of Deep Learning!
This book has by far surpassed my expectations! I have purchased many machine learning and deep neural network books in the past, but nothing has ever come close to this book! First of all, it is written by the fathers of Deep Learning, and is therefore an authority. Secondly, the book is broken into three parts: 1. A math overview and refresher. 2. Deep Learning applications and 3. Research in Deep Learning. I can't help but go through this book from front to back. It is a smooth read, and every sentence written is meaningful. These guys know their stuff! And after you read this book, YOU WILL ALSO know your stuff! If you feel daunted by the price, just remember, you get what you pay for! I'd say they could easily charge about $300+ for this book, but they are doing everyone a very kind favor by ONLY charging this reasonable amount. You get A LOT of bang for your buck with this purchase. I hesitated at first about buying this book because of the price, but I am soooooo happy that I did! Worth every penny! Look no further, get this book and start your Deep Learning journey!!
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Reviewed in the United States on July 14, 2017
M
Verified Purchase
mackster
Carnegie, US
★★★★★ 1
A rushed, poorly written guide of how the "experts" can't really explain what Deep Learning is
Format: Hardcover
This book, in every sense of the word, is rushed. I think the authors wanted to establish themselves as leaders of this young-ish field, but does so by sacrificing quality. It also shows that Deep Learning theory has been there for a long time, known by another name called Neural Networks. The interesting algorithms are of MLP, Back Propagation and the classical neural networks. The optimization methods such as Adam are the ones that are new and interesting, and the only ones worthy of in this book. So, essentially, what you get from this book is use A for X, B for Y and C for Z type of dry, un-intuitive, badly written waste of paper. As for the structure of the book, it's like an example of how not to structure a book. It has some linear algebra, probability at the start (not good enough, and confuses more people and wastes paper). Goes on to prove other algorithms such as PCA (yeah, ok!). Then, talks about how this architecture works for this and that architecture. So, yeah, if you really want to try out deep learning, don't buy this book. Set up Tensorflow/pytorch/ other library, run the tutorials, find an architecture for the problem you are interested in and start tweaking that. You will have far more fun and would have saved your money. The praise that this book gets is beyond me. Did Musk even read this book? I doubt it.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 15, 2018
S
Verified Purchase
Stergios Papadimitriou
Cuba, US
★★★★★ 5
The classic textbook on Deep Learning
Format: Hardcover
Deep Learning is the promising direction towards general purpose effective artificial intelligence. There is an explosion of fruitful research in recent years and a lot of applications pursued mainly from technology giants as Google, Amazon, etc. and outstanding research institutions. The book "Deep Learning " by Ian Goodfellow, Yoshua Bengio, Aaron Gourville, is an excellent piece of work. They manage to present rather difficult things in an understandable manner. The theoretical presentation is outstanding typical of "classic" books. Also, the book stays close to the practical applicability of all the methods and discusses applications extensively. There are a lot of other useful books on deep learning that follow a more practical approach by focusing on a particular deep learning software package, but this one book is certainly much more essential since it provides the required theoretical background in order to be able to do serious work on deep learning. I consider the book as "must have" for anyone that works on deep learning either in an academic or in an industrial environment.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on August 25, 2018

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