SKU: 31863764837
nuna rava compatible stroller

nuna rava compatible stroller Nuna Flex System Frame + PIPA Aire RX Travel System Bundle

Sale price$23.03 Regular price$25.59
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Ships within 48 hours · Estimated delivery Jul 17 - Jul 22

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Description

nuna rava compatible stroller Nuna Flex System Frame + PIPA Aire RX Travel System BundleThe Flex System Frame is travel system readycompatible with the SWIV & TRIV series bassinet, the Flex system stroller seat, and any PIPA series car seat using the included folding ring adapter. With carbon fiber strength and showroom worthy style, the featherlight frame folds in a flash and looks anything but basic. Best of all, it's built for years, not just months. No tricks. No trade offs. Because smart parents want smart systems, not shortcuts or

The Flex System Frame is travel system ready–compatible with the SWIV™ & TRIV™ series bassinet, the Flex system stroller seat, and any PIPA series car seat using the included folding ring adapter.

With carbon fiber strength and showroom-worthy style, the featherlight frame folds in a flash and looks anything but basic.

Best of all, it's built for years, not just months. No tricks. No trade-offs. Because smart parents want smart systems, not shortcuts or clunky compromises.

Features

  • Carbon fiber reinforced aluminum frame
  • Sleek carbon fiber weave pattern
  • Ultra-lightweight and durable
  • Height-adjustable 3-position pivoting handle
  • 1-hand compact fold
  • Stands when folded
  • Folds with adapter
  • Luxe leatherette pushbar
  • Birth to 50 lbs
  • Large puncture-proof tires
  • 1-touch rear-wheel brakes
  • All-wheel suspension
  • Large basket holds up to 22 lbs
  • Tracking device pocket
  • Carry bag included
  • Travel system ready–compatible with the SWIV™ & TRIV™ series bassinet, the
  • Flex system stroller seat, and any PIPA series car seat using the included folding ring adapter

Specifications

Product weight:

  • Frame: 8.5 lbs
  • Frame + Adapter: 11.3 lbs

Recommended Usage

  • Up to 50 lbs (when used with Flex system seat, sold separately)

Nuna PIPA Aire RX Infant Car Seat + PIPA RELX Base with Load Leg

Who says security can't be super stylish?

Lighten your load and up your style game. That's the PIPA aire rx motto. Whether it's the sleek design elements or the smart security features that catch your eye, the PIPA aire rx car seat is all about hassle-free adventures with all the perks.

Light on weight, heavy on style, it’s your go-anywhere, do-anything partner that’s in it for the long haul. In the world of PIPA aire rx, casual meets cool, and carrying less is the ultimate flex.

Now, you can carry less, do more, and look good doing it. Your refined taste for baby adventures deserves an equal match.

Features

PIPA aire rx

  • The PIPA aire rx is lightweight with zero compromises
  • A lightweight full-featured infant car seat
  • Ideal for city living and taxis as it can be installed with a vehicle seat belt and no base
  • Integrated magnetic buckle holders keep straps out of the way when buckling baby in
  • Fabrics and inserts are conveniently machine washable
  • FAA certified for aircraft use with or without a base
  • Connects with all Nuna strollers to create a stylish travel system*
  • 5-second steel-reinforced True lock™ installation makes set up swift, simple, and safe**
  • Side Impact Protection (SIP) for ultimate baby safekeeping
  • Open belt path with lock off secures lap and shoulder belt
  • Features Aeroflex™ foam that is cleverly lightweight, resilient, and minimizes force transferred to baby
  • 3-position height-adjustable headrest and 5-point harness keeps little ones in place
  • Removable infant head and body inserts nestle baby in comfort and security
  • Tailor tech™ memory foam seat panel and headrest provides a comfortable custom fit
  • UPF 50+ canopy with 2 positions and a flip-out eyeshade protects from sun exposure
  • The iconic Sky drape™ provides baby with ultimate privacy for quiet moments
  • Soft yet durable micro-knit fabric for refined style and casual warmth
  • Super-resilient top-of-the-line plastics for a heavy-duty secure shell
  • Exposed aerospace aluminum handle adds a contemporary aesthetic and enhances the seat's intuitive functionality
  • Luxe leatherette carry handle for more secure gripping
  • From fabric to foam and beyond each element is smartly sourced to be both flame-resistant and contain no added fire-retardant chemicals making it safer for baby
  • Infant head and body inserts are made of environmentally friendly Merino wool and TENCEL™*** lyocell fiber blend that is soft, naturally controls moisture, and is environmentally friendly
  • GREENGUARD Gold Certified to meet some of the world's most rigorous third-party chemical emissions standards, and certified to not contribute to indoor air pollution or chemical exposure
  • Additional GOTS organic cotton infant insert and harness cover set

RELX base

  • True lock™ rigid latch is 50% stronger than a typical belt latch
  • 4 bubble-free recline positions deliver customized comfort
  • Integrated anti-rebound panel provides an additional layer of rear-facing security
  • 4-position rigid latch adjusts to reduce or remove the gap between vehicle seat and base
  • Multi-position steel stability leg reduces forward rotation and telescopes for improved range of fit in more vehicles and middle seating positions
  • Crumple zone within the stability leg absorbs impact and minimizes force transferred to baby
  • Colored installation indicators confirm correct connections
  • Low profile base for super easy loading
  • Easy vehicle seat belt install provides options
  • Latch and stability leg neatly store away when not in use
  • Anchor latch guides make it easy to locate and install on lower anchor bars

*And their adapters

**When used with Nuna PIPA RELX base
***TENCEL™ is a trademark of Lenzing AG

Specifications

  • RECOMMENDED USE: 4 to 30 lbs and 16-30 in.
  • Car seat dimensions L 27.25 in x W 17.5 in x H 23 in
  • WEIGHT: 6.2 lbs (without canopy and inserts - canopy and inserts approx. 2.2 lb)
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: 31863764837

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William P Ross
Louisville, 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
Charlottesville, 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
Alexandria, 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
Waukegan, 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
Massapequa, 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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