SKU: 53750880992

Karibu Sauna Bodin ohne Ofen, mit Dachkranz, mit energiesparender Saunatür

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Karibu Sauna Bodin ohne Ofen, mit Dachkranz, mit energiesparender SaunatürProdukteigenschaften Karibu Elementsauna Bodin 68 mm ohne Ofen: Wnde: Die Wandelemente der Karibu Elementsauna bestehen aus einer 68 mm starken, stabilen Konstruktion. Durch diese Bauweise wird ein einfacher Aufbau der Systemsauna garantiert es sorgt fr eine hohe Stabilitt. Die Wandelemente bestehen aus einer stabilen Rahmenkonstruktion mit zwischengelagerter 42 mm starker Mineralwolldmmung. Die Innenseiten bestehen aus 12,5 mm starkem Spezial Fichte

Produkteigenschaften Karibu Elementsauna Bodin 68 mm ohne Ofen:

Wände:
Die Wandelemente der Karibu Elementsauna bestehen aus einer 68 mm starken, stabilen Konstruktion. Durch diese Bauweise wird ein einfacher Aufbau der Systemsauna garantiert es sorgt für eine hohe Stabilität. Die Wandelemente bestehen aus einer stabilen Rahmenkonstruktion mit zwischengelagerter 42 mm starker Mineralwolldämmung. Die Innenseiten bestehen aus 12,5 mm starkem Spezial-Fichte-Profilholz. Dieser Aufbau garantiert eine optimale, saunagerechte Isolierung. Die sichtbaren Außenseiten sind ebenfalls mit Profilholz verkleidet. Die nicht sichtbaren Seiten sind mit einer Hartfaserplatte verstärkt und weisen eine Gesamtstärke von 57 mm auf.

Dach:
Die Dachelemente der Karibu Elementsauna sind ähnlich zu den Wandelementen aufgebaut und bestehen aus einer stabilen 57 mm starken Konstruktion. Durch diese Bauweise wird ein einfacher und schneller des Daches garantiert es sorgt für eine hohe Stabilität. Die Dachelemente bestehen aus einer stabilen Rahmenkonstruktion mit zwischengelagerter 42 mm starker Mineralwolldämmung. Die Innenseiten bestehen aus 12,5 mm starkem Spezial-Fichte-Profilholz. Die Außenseiten sind mit einer Hartfaserplatte verstärkt. Das Dach dieser Karibu Sauna Bodin wird durch einen schönen Dachkranz auf 2 Seiten abgeschlossen. Dieser Dachkranz verfügt über 3 LED-Spots inkl. Trafo. Dieser muss über eine freie Steckdose angeschlossen werden.

Liegen:
Die Karibu Saunaliegen bestehen aus hochwertigem Espenholz und sind mit bis zu 250 kg belastbar. Die vormontierten Liegen werden aus Espenholz gefertigt, da dieses eine geringere Wärmeleitfähigkeit aufweist und somit nicht zu heiß wird um darauf zu sitzen oder zu liegen. Ferner ist das Espenholz nahezu astfrei und bietet somit eine edle Optik. Die Front der Liegen, welche in einem Rahmen aus Fichtenholz eingelassen werden, ist mit Spezial-Espenholz optisch hervorgehoben.

Tür:
Die energiesparende Saunatüre ist eine wärmegedämmte Saunatüre aus Holz mit einem Türrahmen aus Massivholz. Sie hat ein Durchgangsmaß von 173 x 64 cm und ist mit einem Lichtausschnitt in der Größe 161 x 24 cm versehen. Der Karibu Türgriff ist lackiert und rundet das edle Erscheinungsbild ab. Für ein optimales Schließen der Türe verfügt die Tür und der Rahmen über eine Rollverschlusstechnik.

Saunaholz:
Nordische Hölzer zählen traditionell zu den besten Hölzern im Saunabau. Durch die extremen Klimaverhältnisse wird ein sehr langsamer Wuchs bewirkt, das das Holz insgesamt "fester" macht. Die sichtbaren Jahresringe stehen enger zusammen, das Holz ist dichter, fester, dauerhafter und somit für die großen Temperaturschwankungen in einer Sauna besonders gut geeignet. Aufgrund der geringen Wärmeleitfähigkeit der verwendeten Hölzer können Sie zum Beispiel die Bänke problemlos während eines Saunabades berühren.
Artikelnummer: 75630

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SKU: 53750880992

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4.3 ★★★★★
Based on 29 reviews
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Shannon
Massapequa, US
★★★★★ 5
The best DL/ML book I have ever seen!!
Format: Hardcover
Fantastic deep-learning book! The logic is very easy to follow, but the content is very thorough when it comes to explaining the theories behind it, making it perfect for beginners as well as math and CS students. The best DL/ML book I have ever seen!!
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Reviewed in the United States on November 30, 2025
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William P Ross
Fort Morgan, 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
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Adam
Draper, 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
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Amazon Customer
Pawtucket, 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
Birmingham, 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

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