SKU: 11380712250
cybex sirona 2020

cybex sirona 2020 CYBEX SIRONA G I-SIZE PLUS Car Seat

$25.17 $27.97
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Description

cybex sirona 2020 CYBEX SIRONA G I-SIZE PLUS Car SeatPlease note: this item is not stocked in store and will be delivered in 3 5 working days. The latest car seat in our successful Sirona line is the most comfortable yet: the Sirona Gi i Size. Extended rear facing for safer travel up 20kg, this car seat also features integrated Linear Side impact Protection for defense from all directions. A range of innovative features also upgrade your childs comfort, including 360 rotation in any recline position

Please note: this item is not stocked in store and will be delivered in 3-5 working days.

The latest car seat in our successful Sirona line is the most comfortable yet: the Sirona Gi i-Size. Extended rear-facing for safer travel up 20kg, this car seat also features integrated Linear Side-impact Protection for defense from all directions.

A range of innovative features also upgrade your child’s comfort, including 360° rotation in any recline position with the easy rotation handle, for smooth on and off boarding. Innovative all-round air ventilation means the ride stays cool, and you have the option of choosing mesh fabrics for maximum breathability with the Plus fabric version.

Five recline positions are available in either direction ‒ tailored comfort for your child, whether they’re a tiny newborn or a fully-grown four-year-old (newborn inlay accessory sold separately). 360° of comfort and safety for their first four years: the Sirona Gi i-Size.

CYBEX were awarded Which? Baby and Child Brand of the Year in 2024!

Features:

Up To 50% Higher Safety Levels*

Extended rear-facing – one of the safest ways to travel in a car seat. In the critical first moments of a frontal impact, the child’s body is pushed against the padded car seat shell. This keeps movement to a minimum and reduces force acting on the child’s neck. Mandatory up to 15 months (76 cm), we recommend keeping your child rear-facing for as long as possible. The Sirona Gi i-Size is designed for your child to sit comfortably rear-facing until they weigh 20 kg.

*compared to the same seat forward-facing in a frontal crash. Result of internal testing using 2022 ADAC frontal crash test criteria.

Quick And Easy Onboarding

A stress-free start to your journey. Just swivel the car seat using the easy rotation handle to face the car door and get your child onboard, in any recline position. You can avoid back strain, while your child stays comfortable in the recline position that fits them, whether they’re a newborn or a toddler. Switching from rear to forward-facing travel is just as easy.

Optimal Breathability

The all-round air ventilation of Sirona Gi i-Size allows air to flow through ventilation channels within the car seat, carrying away heat and helping avoid a hot and sweaty ride for your little one. Choosing the mesh fabric available on the Plus version increases airflow even more – with up to 6 times more breathability than comparable car seat fabrics. The clear choice for comfort in any season.

Easy Onboarding

When you’re getting your child strapped into the car seat, you need all the help you can get. The Sirona Gi i-Size features ingenious loops designed to keep the harness out of the way as you get your child onboard.

Grows With Your Child Up To 4 Years Old

As your baby grows, adjust the Sirona Gi i-Size headrest for a comfortable fit at every stage. 12 positions allow a tailored fit to your child, with the harness lengthening automatically with each adjustment. And it can be adjusted with one hand for extra ease of use.

Side-protection

The Linear Side-impact Protection defends your child against the force of a side impact. Working together with the energy-absorbing shell, the L.S.P. System significantly reduces the effect of impact force on the child.

Always In A Comfortable Position

For every moment, whether your little one is a newborn or a growing child, the ideal recline setting is available in both riding directions – and in the boarding position, too. And when your child falls asleep in the seat, you can recline it with one hand, letting them dream that little bit longer.

Straightforward Installation

It only takes moments to set up your Sirona Gi i-Size. Use an ergonomic handle to click the ISOFIX into the vehicle seat and extend the load leg down to the car floor. Both provide stability and extra safety in the event of an accident. Visual indicators help you confirm the seat is ready to protect.

Specifications:

  • Regulation: UN R129/03
  • Child Height: 61 - 105 cm (From 40 cm with newborn inlay)
  • Child Weight: Max. 20 kg; from approx. 3 months up to 4 years (From birth with newborn inlay)
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SKU: 11380712250

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4.2 ★★★★★
Based on 29 reviews
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William P Ross
Houston, 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
Dallas, 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!!
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Reviewed in the United States on July 14, 2017
M
Verified Purchase
mackster
Louisville, 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
Port Orchard, 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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