SKU: 6955312386
freitragende markise

freitragende markise Horntools Freitragende 180 Grad Markise Horizon – dachzeltstore.at

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Description

freitragende markise Horntools Freitragende 180 Grad Markise Horizon – dachzeltstore.atDie innovative 180 Markise Horizon von horntools ist eine der leichtesten freitragenden Markisen auf dem Markt und bietet eine Reihe spannender Features fr perfekten Schutz whrend deiner Abenteuer. Produkthighlights: Komplett freitragend: Keine zustzlichen Sttzen erforderlich Extrem leicht mit nur 18 kg: Flexibel genug fr die Montage auf Dachtrgern und Dachzelten Aufbau in unter 3 Minuten Integrierte dimmbare Beleuchtung fr die perfekte Lichtstimmung

Die innovative 180° Markise Horizon von horntools ist eine der leichtesten freitragenden Markisen auf dem Markt und bietet eine Reihe spannender Features für perfekten Schutz während deiner Abenteuer.

Produkthighlights:

- Komplett freitragend: Keine zusätzlichen Stützen erforderlich
- Extrem leicht mit nur 18 kg: Flexibel genug für die Montage auf Dachträgern und Dachzelten
- Aufbau in unter 3 Minuten
- Integrierte dimmbare Beleuchtung für die perfekte Lichtstimmung am Abend
- Alles Zubehör inklusive in praktischen Aufbewahrungstaschen
- Verstärkte Gummi-Patches schützen die Aufsteller vor Wasseransammlungen
- Verpackt 2.0 Meter lang

Genieße uneingeschränkte Freiheit mit der komplett freitragenden Konstruktion unserer Markise. Du benötigst keine zusätzlichen Befestigungen oder Stützen – platziere sie einfach an deinem gewünschten Ort und erfreue dich an ihrem robusten Design.

Leichtgewichtig und schnell aufgebaut:
Mit nur 18 kg ist unsere freitragende Markise unglaublich leicht und dennoch äußerst stabil. Der Aufbau ist im Handumdrehen erledigt dank einer intelligenten Konstruktion, die Zeit und Mühe spart. Verwandle deinen Außenbereich in Sekundenschnelle in eine komfortable Oase.

Alles Zubehör inklusive:
Unsere Markise wird mit allem geliefert, was du benötigst, um sofort loszulegen. Kein lästiges Suchen nach zusätzlichem Zubehör – alles, von den Befestigungselementen bis hin zu den praktischen Bedienungsanleitungen, ist im Lieferumfang enthalten. Dein Komfort steht für uns an erster Stelle.

Dimmbare Beleuchtung inklusive:
Tauche deine Outdoor-Umgebung in eine angenehme Atmosphäre mit unserer integrierten dimmbaren Beleuchtung. Passe die Beleuchtung deinen Bedürfnissen an und schaffe die perfekte Stimmung für entspannte Abende im Freien oder gesellige Feiern.

Montage am Dachträger:
Die Seitenmarkise ist mit dem ExRoof Dachträger sowie mit Dachträgern anderer Anbieter kompatibel. Eine universale Markisenhalterung ist im Lieferumfang enthalten. Die Schrauben können horizontal verschoben und passgenau auf deinen Dachträger eingestellt werden. Eine Montage auf Dachträgern mit T-Nut ist ebenfalls möglich. Wenn du die Markise auf einem horntools ExRoof Dachträger montieren möchtest, bieten wir zusätzlich eine ExRoof Markisenhalterung an.

Lieferumfang:

- Seitenmarkise inklusive Schutzhülle
- 2 x Teleskop-Stützstange (schwarz)
- Spannseile mit Haken & Heringe
- Universale Markisenhalterung (für Dachträger)
- Serviceanleitung

Technische Daten:

- Fläche der Markise (geöffnet): 6 m²
- Gewicht der Markise: 18,75 kg
- Länge der Markise (geöffnet): 2 m
- Größe der Markise (verpackt): 2155 x 220 x 200 mm
- Material der Markisenarme: Aluminium
- Stofffarbe: Grau
- Material des Stoffs: 280gsm Poly-Cotton
- UV-Schutz: UPF 50+
- Wassersäule: 3000 mm
- Länge der Teleskop-Stützstange (min): 1,4 m
- Länge der Teleskop-Stützstange (max): 2,4 m
- Gewicht der Teleskop-Stützstange: 1,5 kg
- Material der Teleskop-Stützstange: Aluminium
- Farbe der Teleskop-Stützstange: Schwarz
- Zulässige Windgeschwindigkeit: bis 30 km/h freitragend und 60 km/h mit Teleskop-Stangen und Abspannseilen
- Abspannung: per Schnellspannmechanismus mit Ratsche & Karabiner

Shipping Notes
  • Free Standard Shipping on $100+ Orders to the USA.
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SKU: 6955312386

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4.3 ★★★★★
Based on 24 reviews
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William P Ross
Boise, 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
Alexandria, 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
Dallas, 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
Natrona Heights, 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
Lexington, 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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