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Description
cybex assistance Cybex e-Gazelle S Electronic Assist Single-to-Double Strollere GAZELLE S RECOGNIZED BY TIME BEST INVENTIONS 2024. A stroller for all your adventures ahead. The CYBEX e Gazelle S stroller combines adaptability and convenience with the electric power of smart technology. Conquer any uphill climb or downhill descent and cruise through any uneven terrain effortlessly with the assistance of our electronic power on demand. Adapting to the changing needs of your family, the e Gazelle S is designed to support 20+
e-GAZELLE S RECOGNIZED BY TIME BEST INVENTIONS 2024.
A stroller for all your adventures ahead.
The CYBEX e-Gazelle S stroller combines adaptability and convenience with the electric power of smart technology. Conquer any uphill climb or downhill descent and cruise through any uneven terrain effortlessly with the assistance of our electronic power on demand. Adapting to the changing needs of your family, the e-Gazelle S is designed to support 20+ different configurations and easily converts from a single to double stroller. Whatever your plans are for the day, you can rely on the shopping basket and spacious lower basket for up to 55lbs. of groceries or any essentials for the journey ahead. After a long busy day, use our gentle rocking feature to help calm and soothe your child.
- SMART ASSIST MODE: Forward power and downhill break assist mode helps control how much assistance you need with the convenient lever on the handlebar, no phone application required for use
- ROCKING FEATURE: Choose between three gentle settings to soothe your child
- SMART SAFETY: Includes a two-step safety delay start mode
- SINGLE TO DOUBLE: Easily converts from a single to double stroller without additional adapters
- 20+ CONFIGURATIONS: Add a second Gazelle S Seat unit, Gazelle S Cot, or any CYBEX Infant Car Seat to meet your needs. (sold separately)
- EASY FOLD: Folds with two seat units attached to the frame
- ONE-PULL HARNESS: Our user-friendly harness system makes securing your child in the seat a breeze with one simple pull – no fuss and extra handy if you’re doing it twice
- ONE-HAND ADJUSTABLE RECLINE: Independent reclining seat back and leg adjustments offer multiple configurations, allowing you to position your child for comfort
- SHOPPING BASKET: removeable and provides extra storage up to 25 lbs.
- LOWER BASKET: Extra-large, easy access lower basket for extra storage space while out on the go (30 lbs. max load)
- PREMIUM DESIGN: Made with a robust all-aluminum frame, leatherette handlebar and bumper bar, and high-quality fabrics
- SMOOTH ALL-WHEEL SUSPENSION: All-wheel suspension with integrated frame shock absorption system provides a smooth ride over a variety of surfaces
- XXL SUN CANOPY: Extendable XXL sun canopy with mesh window and a UPF 50+ rating
- REVERSIBLE SEAT UNIT: Large, reversible seat unit reclines to a near-flat position
- WEIGHT CAPACITY: 50 lbs. weight capacity for each seat unit (second seat unit sold separately)
- HEIGHT-ADJUSTABLE HANDLEBAR: One-hand, height-adjustable handlebar offers comfortable steering for all users
- TRAVEL SYSTEM READY: Versatile 3-in-1 Travel System with the seat unit, Gazelle S Cot (sold separately), and any CYBEX Infant Car Seat (sold separately) using the included adapters
- COMPTABILITY: Stroller compatible with CYBEX, Maxi-Cosi® Mico 30 and Nuna PIPA™ infant car seats using the included adapters
Additional adapters sold separately for: BRITAX® B-Safe 35, BRITAX® B-Safe 35 Elite, BRITAX® Endeavors, Graco® SnugRide® 30/35, Graco® SnugRide® SnugLock® 30/35, Chicco® KeyFit® 30, Peg Perego® Primo Viaggio 4-35. Please contact ParentLink for additional compatibility information.
Accessories available for purchase: Gazelle S Second Seat, Gazelle S Cot, Any CYBEX Infant Car Seat, Snack Tray, Parasol, and Summer Seat Liner
Wheel information
- Stroller Brakes: Foot pedal parking brake
- Lock/Swivel Wheel: Lockable front swivel wheels, lockable rear wheels
- Stroller Wheel Type: Foam Filled Tires
- Front Wheel Diameter: 7.9"
- Rear Wheel Diameter: 11"
What's in the box
- eGazelle Stroller Frame
- 1 Seat Unit
- Bumper Bar
- Shopping Basket
- Battery Pack
- Charger
- Rain Cover
- Car Seat Adapters
- Cup Holder
Recommended usage
- Suitable from 3 months to 50 lbs.
Specifications
- Dimensions (open): 42.3"L X 26"W X 43.3"H
- Dimensions (folded): 32.3"L X 26"W X 15.3"H
- Weight: 32.4
Materials
- 65% Aluminum
- 15% Polyester
- 15% Plastic
- 5% Rubber
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- Free Standard Shipping on $100+ Orders to the USA.
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Exchange/Return Notes
- We offer a 30-day return/exchange service after receiving.
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4.7 ★★★★★
Based on 1333 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