SKU: 49923945283
notch tent

notch tent TARPTENT Notch – Outdoorline

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Description

notch tent TARPTENT Notch – OutdoorlineTarptent Notch is a highly versatile and ultralight solo tent, weighing just 792 g, intended for solo hikers who prioritize both minimal weight and versatility in their shelter. It stands out with its dual Apex design, which not only provides ample interior space but also ensures a compact footprint, making it particularly suited for use in dense forested areas where space is limited. The tent's structure includes two doors and two vestibules,

Tarptent Notch - is a highly versatile and ultralight solo tent, weighing just 792 g, intended for solo hikers who prioritize both minimal weight and versatility in their shelter. It stands out with its dual Apex design, which not only provides ample interior space but also ensures a compact footprint, making it particularly suited for use in dense forested areas where space is limited. The tent's structure includes two doors and two vestibules, offering convenience and accessibility. Additionally, the tent's components, comprising a 451 g rain fly and a 292 g inner mesh, can be used either independently or together, providing flexibility for a variety of weather conditions and camping preferences.

One of the key features of the Notch is its superior ventilation system, designed to ensure comfort in a range of climates. The tent includes adjustable side doors and end ports, allowing campers to regulate airflow effectively. This is particularly useful for preventing condensation and maintaining a comfortable internal environment. The inner mesh, equipped with a bathtub floor, adds another layer of protection, especially in buggy or damp conditions. The tent's interior is thoughtfully designed to accommodate users up to 188 cm in height, with enough headroom to sit up comfortably, which is a notable achievement given the tent's ultralight nature. There is also sufficient space for storing small items, making it practical for extended trips.

Setting up the Notch is straightforward, requiring only two trekking poles, which most hikers already carry, making it an efficient and space-saving shelter option. The tent is also equipped with line-locs, which enhance its stability in windy conditions by allowing for a taut pitch. Weighing in at just 792 g, the Tarptent Notch is highly recommended for solo hikers who need a shelter that is both lightweight and adaptable to a wide range of environments. Its design allows it to function as a standalone fly, inner mesh, or full double-wall tent, making it suitable for diverse conditions, from wet, bug-infested forests to dry, windy deserts. The Notch strikes an excellent balance between weight, livability, and versatility, making it a valuable addition to any solo hiker's gear.

For tent setup you will need: 2x trekking pole 107-115cm (42-45in) or 2x Tarptent Carbon PolyPole

Interiors (mesh or solid) are interchangeable and clip in and out from underneath the fly. The solid interior has 2/3 solid, 1/3 mesh walls and a solid roof and blocks horizontal blowing wind, sand, snow, and rain. It makes the tent up to 14°C (8°F ) warmer in calm winds.


Package includes:
  • Notch fly, with struts, cording, and apex guylines
  • Notch mesh or solid interior
  • Four Easton® Nano 152 mm / 6 in aluminum stakes
  • Stake bag
  • Tent bag

Seams aren't sealed. We recommend to use GEAR AID Seam Grip SIL seam sealer to achieve complete waterproofness. We do not offer seam sealing service at this time. It is important to note that seam sealed products can no longer be returned within 30 days. However, the product is still under warranty.




MATERIAL
Fly Material: 20D nano ripstop 100% silicone coated polyester rated to over 5,000mm hydrostatic head, forest green
Floor Material: 30D double ripstop 100% silicone coated nylon 66 rated to over 5,000mm hydrostatic head, black
Fly Zippers: YKK #3 Aquaguard waterproof dual pull
Mesh: 15D nylon no-see-um mesh 
Solid Fabric: Breathable and windproof 10D ripstop nylon
Guyline/Cording:  2.5mm reflective sheath with Spectra® core and integrated LineLoc’s
Stakes: Four 15 cm / 6 in Easton® Nano aluminum stakes, made in USA
Rigid Struts: Four 41 cm / 16 in pultruded carbon fiber, made in USA


WEIGHT: 792 g / 27.95 oz (polyester fly with solid interior, including stakes, struts, stuff sack, bags, and apex guy lines)

SEASONS: 3 - 4

PACKED SIZE: 41 cm x 9 cm / 16 in x 3.5 in 

FEATURES

  • Constructed with 30D double ripstop nylon 66, 100% silicone-coated, rated over 5,000mm hydrostatic head for exceptional durability and strength, or with 20D nano ripstop polyester, which resists sagging when wet and retains less moisture, also rated over 5,000mm hydrostatic head.
  • Features premium components like YKK zippers, Easton® stakes made in the USA, carbon fiber struts, and Spectra® cording.
  • Excellent wind resistance due to the low-drag shape and small panel sizes, with steep walls designed to shed snow and minimize snow load.
  • Includes integrated interior pockets and clips for organized gear storage, and dual doors with vestibules for easy access and additional storage.
  • Designed with trekking poles that can be positioned tip-up or handle-up using optional adapters, and a double-wall design that prevents condensation.
  • The fly and inner can be pitched separately, and the fly-first pitch design keeps the interior dry when setting up or taking down in the rain.
  • Large, adjustable vents at both high and low points help reduce condensation while offering storm protection when needed.
  • Patented PitchLoc™ carbon fiber strut corners increase stability and interior volume, with removable struts for easy packing.
  • Quick and easy 4-stake pitch can be completed in under 1.5 minutes, with catenary cut curves ensuring a taut, stable setup.
  • Protected entry/exit ensures the interior stays dry during rain, and it accommodates sleeping pads up to 63.5 cm / 25 in wide.
Shipping Notes
  • Free Standard Shipping on $100+ Orders to the USA.
  • Except Preorder products are shipped in 48 hours.
  • Delivery to the USA:
  1. Standard Shipping : 3-10 business days
  • If time is of the essence, please consider selecting expedited delivery for faster service.
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]
  • Please click here for more details>>> Return & Exchange Policy
SKU: 49923945283

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William P Ross
Whiting, 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
Chelsea, 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
Port Orchard, 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
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mackster
Pawtucket, 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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Stergios Papadimitriou
Lake Worth, 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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