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Description
SPD X Austere Cam Strap 5ftThe SPD X Austere CAM UTILITY STRAP features a precision milled T6061 3 4" Cam Buckle and a 5' length of custom woven 3 4" webbing, exclusive to our Special Projects Division. The 5' webbing length will comfortably fit around large duffel bags on roof racks and 20L water cans. Or you can cut down to a shorter length as needed. Weighing in at 8. 2 grams, this CNC machined aluminum buckle is lighter than most plastic side release buckles. Unlike
Plastic buckles would often loosen time and time again, which meant having to dismount to re-fasten gear. Worse yet, any plastic buckles that would fail, puts your gear and mission in peril. At the time he was working on NASA space suit designs and decided to build a better buckle.
Uriel enlisted space in his buddy’s barn, moved in a CNC machine and started designing. After many iterations, the Austere cam buckle was created. It is designed to secure your gear without sacrificing weight. Highly versatile, highly durable, extremely capable buckles and lashing straps with a multitude of uses for securing gear, whether it be bikepacking, backcountry skiing, overlanding, backpacking, or even holding up your pants.
Specifications:
Materials:- T6061 AL
- Titanium 6AL-V4 Grade 5
- Stainless Steel
- High Tensile Strength Nylon
- Length: 5' / 152.4cm
- Width: 0.75" / 20mm
- Buckle: 0.98" Wide x 1.14" Long
- 0.29 oz / 8.2g
- 5' OAL
- High Strength Cam Buckle
- Excellent Webbbing Retention
- Precision Milled from AL Billet
- Cerakote Ranger Green and Orange Cam Colorway
- Custom Ranger Green and Flame Orange 3/4" High Tensile Strength Webbing Exclusive to SPD
- Bar-tack Reinforced
- SPD Woven Label
- Laser Engraved SPD Logo
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4.5 ★★★★★
Based on 29 reviews
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Product Reviews
★★★★★ 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
★★★★★ 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
★★★★★ 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
★★★★★ 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
★★★★★ 5
100% Recommend
Format: Paperback
Invincible Compendium One completely lived up to the hype. From the very first chapter, I was hooked by the story, the action, and the character development. What starts off feeling like a classic superhero story quickly becomes something much deeper, darker, and way more emotional than expected.
The artwork is incredible and the fight scenes are intense without feeling repetitive. Every character feels important and layered, especially Mark and Omni-Man. The pacing is excellent for such a massive collection, and it’s hard to put down once you start reading.
If you’re a fan of superhero comics but want something with real stakes, shocking twists, and strong storytelling, this is absolutely worth reading. Easily one of the best graphic novels I’ve picked up in a long time.
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Reviewed in the United States on May 23, 2026
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