Pay in installments of $5.74 with
,
and
Shipping Estimate
USA
- USA
- CAN
- USA
- CAN
Ships within 48 hours · Estimated delivery Jul 28 - Aug 2
Promo Codes Available:
For Your Every Summer RSVP, with Code: SUMMER15
Description
RDX-160 Presta Tire Pressure Gauge for Bikes (Max 160 PSI) | Road Bike & BMX SeriesThe RDX 160 model is designed for high pressure bike tires (Max 160 PSI) equipped with Presta valve stems. For lower pressure mountain bike tires, please see our MBX 60 (Max 60 PSI) and FTX 30 (Max 30 PSI) gauges. Never be without a reliable high pressure tire gauge for your bike. This rugged air gauge is designed for use on presta valve equipped bike tires that require higher PSI for max performance such as tires common on road bikes, hybrids, and
The RDX-160 model is designed for high pressure bike tires (Max 160 PSI) equipped with Presta valve stems. For lower pressure mountain bike tires, please see our MBX-60 (Max 60 PSI) and FTX-30 (Max 30 PSI) gauges.
Never be without a reliable high pressure tire gauge for your bike. This rugged air gauge is designed for use on presta valve equipped bike tires that require higher PSI for max performance - such as tires common on road bikes, hybrids, and BMX bikes.
This air gauge has been performance tested on the winding roads & trails of the Rocky Mountains, and calibrated to ANSI B40.1 standards (1.5% Mid Scale) for maximum accuracy in the 40-130 PSI range.
Specifications:
- Dial: Analogue 2", Glow-in-Dark
- Working Range: 10-160 PSI
- Max Accuracy Range: 40-130 PSI
- Calibration: ±1.5% (Mid Scale)
- Certification: ANSI B40.1
- Valve Type: Presta*
- Storage Case: Included
* For Presta valve stems only, does NOT work with Schrader valve types.
Recommended Use:
- Road bikes
- BMX
- Hybrid bikes
Key Features:
- Optimized for high pressure bike tires (Max 160 PSI) - performance tested & calibrated accurate to ANSI B40.1 standards (1.5% Mid Scale), ensuring quick & accurate pressure readings without relying on batteries (for use on Presta valves only, NOT compatible with Schrader valves).
- Large, 2" glow-in-dark dial - features easy-to-read scale (10-160 PSI range), providing precise readings that lock-on to the dial face until the pressure reset button is pressed to zero reading. Equipped w/ built-in bleeder valve to release air from overinflated tires & fine tune your tire pressure.
- Rugged durability - feels solid in the hand & shielded by our shock-resistant rubberize gauge head cover, keeping the gauge protected from drops & vibrations, the 90 degree direct Presta valve nozzle lets you easily get in between the bike wheel spokes to measure tire pressure with ease.
- Superior performance - compact & portable design easily stores away in your riding bag or tool kit, so you can always keep your gauge packed for every ride. Includes a hard shell protective zip case to keep your air gauge protected & safe when not in use.
- A must-have for your bicycle tool kit - enjoy longer lasting tires, improved traction, & superior handling on the road or trail thanks to properly inflated bike tires.
Proudly backed by our industry-best 100% Lifetime Warranty!
Order today while supplies last. Limited stock.
100% Free Shipping in the USA!
160 PSI scale too high for your bike? Check out our other Presta tire pressure gauges from this product lineup below!
Shipping Notes
- Free Standard Shipping on $100+ Orders to the USA.
- Except Preorder products are shipped in 48 hours.
- Delivery to the USA:
- 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
4.3 ★★★★★
Based on 14 reviews
Sort
Product Reviews
★★★★★ 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!!
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on November 30, 2025
★★★★★ 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
★★★★★ 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!!
WAS THIS REVIEW HELPFUL?YesReportShare
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.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 15, 2018
recommand products
ROWIE HAVEN BEAD LINEN TANK OAT MARLE
110.00
1EA32 - 3-1/4" Spiral Shank Brite Bulk (50lb)
87.95
Love Love Music Eau De Toilette Spray By Cofinluxe
32.97
CY350041 Wooden Deck for Tamiya 78031 1/350 Scale Japanese Battleship Musashi
17.88
Bracelet de Montre NATO Nylon Gris foncé / Boucle Noir - Souple - Épaisseur 1mm
19.00