SKU: 81797188858

Gabione 100 cm x 90 cm x 30 cm (L x H x T), Maschenweite 5 cm x 10 cm, C-Ring

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Description

Gabione 100 cm x 90 cm x 30 cm (L x H x T), Maschenweite 5 cm x 10 cm, C-RingVerwandle deinen Garten in ein stilvolles Highlight mit dieser hochwertigen Gabione aus galvanisch verzinktem Draht. Ob als Gabionenwand, Steinkorb, Gartenmauer, Hochbeet oder Sichtschutz dieses vielseitige System verbindet modernes Design mit hchster Stabilitt und Langlebigkeit. Die robuste Konstruktion trotzt Wind und Wetter und sorgt fr eine gepflegte, dauerhafte Optik in deinem Auenbereich. Mae: Lnge: 100 cm Hhe: 90 cm Tiefe: 30 cm Technische

Verwandle deinen Garten in ein stilvolles Highlight mit dieser hochwertigen Gabione aus galvanisch verzinktem Draht. Ob als Gabionenwand, Steinkorb, Gartenmauer, Hochbeet oder Sichtschutz – dieses vielseitige System verbindet modernes Design mit höchster Stabilität und Langlebigkeit. Die robuste Konstruktion trotzt Wind und Wetter und sorgt für eine gepflegte, dauerhafte Optik in deinem Außenbereich.

Maße:

  • Länge: 100 cm
  • Höhe: 90 cm
  • Tiefe: 30 cm

Technische Daten:

  • Maschenweite: 5 x 10 cm
  • Drahtstärke: 4 mm
  • Gewicht: 10.4218 kg
  • Steinbedarf: ca. 450 kg
  • Beschichtung: galvanisch verzinkt – zuverlässiger Schutz vor Rost, Korrosion und Witterungseinflüssen
  • Verschlussart: C-Ring

    Verbinde die Gitter schlicht und dezent mit unseren C-Ringen. Hierfür verwendest du die spezielle C-Ringzange (im Lieferumfang enthalten). Montiere die C-Ringe im Abstand von circa 10 cm für einen sicheren Verschluss.

    Die Ringe bestehen – wie auch die Gitter – aus galvanisch beschichtetem Draht. Vor der Montage sind sie C-förmig, nach der Montage bilden sie eine stabile Dreiecksform.

Robuste Konstruktion & geprüfte Qualität

Die Gabione besteht aus stabil verschweißten Gittermatten und ist für höchste Beanspruchungen ausgelegt. Mit einer Zugfestigkeit von über 500 N/mm² und einer Scherfestigkeit der Schweißpunkte von über 3,5 kN überzeugt sie durch enorme Stabilität. Im Salzsprühtest nach DIN EN ISO 9227 wurde eine Beständigkeit von über 3.000 Stunden erreicht – ein klarer Beweis für die hervorragende Qualität und Langlebigkeit.

Einfache Montage & vollständiges Set

Dank des praktischen Verschlusssystems ist der Aufbau deiner Gabione schnell erledigt. Passende Distanzhalter verhindern zuverlässig ein Ausbeulen der Gitter und sorgen für dauerhaft saubere Linien – für ein stabiles und gleichmäßiges Erscheinungsbild.

Vielseitig einsetzbar

Diese Gabione ist vielseitig nutzbar – als Sichtschutz, Gartenmauer, Hochbeet, Hangsicherung oder dekoratives Gestaltungselement. Sie lässt sich mit Natursteinen, Glasbrocken oder Zierkies befüllen und fügt sich harmonisch in jede Gartenlandschaft ein. Ein langlebiger, pflegeleichter und nachhaltiger Blickfang für deinen Außenbereich!

Lieferumfang

6 Gittermatten
C-Ringe zum Verbinden der Gitter
einfache C-Ringzange für die Montage (eine Zange pro Bestellung)
Abstandhalter (verhindern Ausbauchen der Gitter)

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SKU: 81797188858

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4.6 ★★★★★
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William P Ross
Carnegie, 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.
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Reviewed in the United States on March 15, 2017
A
Verified Purchase
Adam
Charlottesville, 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.
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Reviewed in the United States on May 22, 2026
A
Verified Purchase
Amazon Customer
Massapequa, 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
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mackster
Battle Creek, 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.
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Reviewed in the United States on May 15, 2018
S
Verified Purchase
Stergios Papadimitriou
Battle Creek, 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.
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Reviewed in the United States on August 25, 2018

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