SKU: 2587484751
grey bugaboo fox

grey bugaboo fox Bugaboo Fox 5 Renew with Cybex Cloud T Travel System Bundle - Moon Gre

$25.48 $28.31
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Description

grey bugaboo fox Bugaboo Fox 5 Renew with Cybex Cloud T Travel System Bundle - Moon GreBugaboo Fox 5 Renew The ultimate go anywhere pushchair, more consciously crafted Inspired by nature, made to nurture Embrace nature with the Bugaboo Fox 5 Renew. Our iconic all terrain pushchair carries your baby in unparalleled comfort, and the two in one system grows with them. Elevated for effortless styling, its also mindfully crafted with more sustainable materials. Need to know features Our next generation pushchair offers unmatched

Bugaboo Fox 5 Renew
The ultimate go-anywhere pushchair, more consciously crafted

Inspired by nature, made to nurture
Embrace nature with the Bugaboo Fox 5 Renew. Our iconic all-terrain pushchair carries your baby in unparalleled comfort, and the two-in-one system grows with them. Elevated for effortless styling, it’s also mindfully crafted with more sustainable materials.

Need-to-know features
Our next-generation pushchair offers unmatched manoeuvrability on any terrain, giving you the freedom to go further together. The two-in-one design lets your baby go from carrycot to seat, so they can enjoy exceptional comfort at each stage of their journey.

Effortless on any terrain​
Explore the outdoors with ease. The extra-large puncture-proof wheels and advanced suspension offer the smoothest strolls, wherever you go, so you can coast over cobbles or rougher terrain without disturbing your baby.​​

Unrivaled manoeuvrability​
Experience best-in-class navigation. At 12.3 kg fully assembled, the pushchair’s light yet sturdy so you can steer with a touch and stay in control. The short wheel distance makes it agile and responsive, ready for wherever your journey takes you.​

Crafted for superior comfort​
Create a nurturing space for your newborn in the large all-season carrycot with breezy panels. The extra-breathable PureBreeze™️ mattress has antibacterial protection, and the summer and winter sides help regulate your baby’s temperature for restful naps.

Easy to use with one hand
Engineered to make every day easier. With just one hand, you can adjust the handlebar, recline the seat, and even fold the pushchair — ideal when there’s plenty to juggle on your journey.​

Grows with your baby
The Bugaboo Fox 5 Renew is ergonomically designed for your baby’s development. The toddler seat has a super-soft five-point harness and extends up to 10 cm. It features three recline positions, and you can adjust the seat to face you or the world.

Materials for the future​
To reduce its impact on our planet, the pushchair’s more sustainably crafted with durable recycled fabrics, bio-based material, and recycled aluminium. By making conscious choices, we’ve cut its CO2 footprint by 30% compared to past Bugaboo Fox models.​

Rooted in responsibility​​
A long-lasting product is a more sustainable one. The Bugaboo Fox 5 Renew is crafted with premium materials under safe and fair conditions in our award-winning factory. It’s then tested beyond industry standards for superior safety and durability.

What's included
Chassis incl. wheels and leather look grips
Seat / bassinette frame,
Seat hardware incl. footrest,
Seat fabric with comfort harness
Rotating carry handle
Sun canopy wires, sun canopy clamps, sun canopy (with peek-a-boo)
Wheel caps
Underseat basket
Rain cover
carrycot fabric set
carrycot bottom
Aerated mattress
carrycot stiffeners

Car seat compatability
Bugaboo Turtle Air by Nuna, Nuna Pipa Next, Cybex Aton M, Cybex Aton 5, Britax Römer Baby Safe3 i Size, Cybex Cloud Z2, Kiddy Evolution Pro 2, BeSafe iZi Go X1, BeSafe iZi Go Modular X1, Axkid Modukid Infant, Maxi-Cosi Pebble, Maxi-Cosi Coral 360, Cybex Cloud Z2

Specifications:

Product dimension L x W x H
Most compact folded product dimensions
89 x 53 x 34 cm

Unfolded (width)
60 cm

Product capacity under seat bag
39 liters 10.3 gal

Product weight
10.4 -12.6 kg

Shipping Notes
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Exchange/Return Notes
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SKU: 2587484751

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4.2 ★★★★★
Based on 25 reviews
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Verified Purchase
William P Ross
Dallas, 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.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on March 15, 2017
A
Verified Purchase
Adam
Carnegie, 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.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 22, 2026
A
Verified Purchase
Amazon Customer
Omaha, 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!!
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on July 14, 2017
M
Verified Purchase
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.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 15, 2018
S
Verified Purchase
Stergios Papadimitriou
Birmingham, 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.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on August 25, 2018

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