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Description
stokke green stroller Stokke YOYO³ Stroller From Newborn to ToddlerOne stroller for all stages: start with the 0+ newborn pack and switch to the 6+ color pack as your baby grows. Stokke YOYO is a versatile stroller that accompanies your child every day, from birth to toddler. Sturdy and super maneuverable, it has been designed to provide optimal daily comfort to your child. Stokke YOYO has double the agility and ingenuity with its signature folding and unfolding. It can be stored in the smallest space at home, takes
One stroller for all stages: start with the 0+ newborn pack and switch to the 6+ color pack as your baby grows.
Stokke® YOYO³ is a versatile stroller that accompanies your child every day, from birth to toddler. Sturdy and super maneuverable, it has been designed to provide optimal daily comfort to your child. Stokke® YOYO³ has double the agility and ingenuity with its signature folding and unfolding. It can be stored in the smallest space at home, takes up very little room in the trunk of a car and can be worn over the shoulder. Catch the subway, get on a bus, jump in a taxi or fly to the other side of the world! Clip a compatible car seat on your YOYO stroller easily. There has never been a more convenient stroller. New features: extended canopy, ventilation window, peek-a-boo window and super soft cushion.
Stokke® YOYO³ stroller from 6 months
- Versatile, ultra compact & super sturdy, providing optimal daily comfort from 6 months.
- Folds in and out in a flash
- Compact, can be stored anywhere
- Suitable for air travel, folded (cabin baggage dimensions*)
- Ultra-lightweight, easily carried over the shoulder
- Extendable anti-UV canopy with peak-a-boo and closeable ventilation window
- Equipped with a 5-point harness
- Redesigned seat pad: new pillow and increased backrest height with mesh strap protectors
- Sturdy and super maneuverable with reflecting wheels for added safety
Increased child comfort
- 4 wheel suspension (Hytrel® elastomer technology) and "Soft Drive" system
- Extra storage: under seat basket with 10kg/22lbs capacity and zipped back pocket to keep essentials close at hand
- Foldable handlebar in soft faux leather with tether strap
- Multi-position reclining backrest
- Anti-UV (UPF 50+) water-repellent fabric
Includes
- 1 stroller frame
- 1 reversible backrest 1 6+ seat base 1 shopping basket
- 2 6+ canopy wires
- 1 carrying strap
- 1 x protective bag
- Canopy and Seat Pad
*Cabin luggage standards may vary depending on the airline; we recommend checking with your carrier for the latest applicable cabin luggage allowance.
Stokke® YOYO® 0+ newborn pack
- The 0+ newborn pack paired with the YOYO³ frame, allows your baby to lay comfortably flat, snuggled in a soft, cozy nest pad.
- Foldable together with the YOYO³ frame (folded cabin baggage dimensions*)
- Extendable anti-UV canopy with closeable ventilation window.
- Equipped with a 5-point harness.
Extra comfort
- 2.5cm mattress with soft headrest.
- This version lets you clip your car seat onto the stroller frame without having to remove the fabric. Anti-UV (UPF 50+) water-repellent fabric.
- Accommodates newborns from birth and up to 9kg/19.8 lbs.
Includes
- 1 head support
- 1 base fabrics
- 1 nest pad
- 1 canopy
- 1 foot cover
- 1 canopy wire
*Cabin luggage standards may vary depending on the airline; we recommend checking with your carrier for the latest applicable cabin luggage allowance.
YOYO car seat adapters
- Allow you to clip compatible car seats on the YOYO³ stroller.
- These are the compatible car seats you can use with the car seat adapters:
- Nuna Pipa Lite
- Clek Liing
- Cybex Aton Q
- Maxi Cosi Mico Max Plus
- Pipa Nuna
- Cybex Aton2
- Cybex Cloud Z
- Cybex Aton5
- Maxi-Cosi Max Mico 30
Specifications
- Dimensions: 41.7L x 33.8W x 17.3H in.
- Weight: Full stroller with 0+ newborn pack 14.6 lbs.
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- We offer a 30-day return/exchange service after receiving.
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4.1 ★★★★★
Based on 20 reviews
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Product Reviews
★★★★★ 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
★★★★★ 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
★★★★★ 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
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