SKU: 71115986270
stokke tripp trapp australia

stokke tripp trapp australia Stokke Tripp Trapp Chair

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Description

stokke tripp trapp australia Stokke Tripp Trapp ChairTripp Trapp elevates a child to the optimal and correct seating position. Designed to bring children closer to the table, the Tripp Trapp by Stokke allows the child to sit, eat and interact with other family members whilst seated. Sitting with mums and dads, the child can bond and develop language and social skills. Features: Brings your baby to the dining table and closer to the family Adjustable seat and footplate for optimal ergonomics Wipes clean

Tripp Trapp elevates a child to the optimal and correct seating position. Designed to bring children closer to the table, the Tripp Trapp by Stokke allows the child to sit, eat and interact with other family members whilst seated. Sitting with mums and dads, the child can bond and develop language and social skills.

Features:

 

Tripp Trapp's design, including adjustability of the seat plate and footrest in height and depth, enables correct ergonomic sitting. Ergonomically correct seating position improves posture and support to a child’s developing spine whilst providing legs and feet with full freedom of movement for the adjusting and shifting of body weight.

Both the seat plate and footrest can be adjusted in height and depth. Helps the child be seated safe and comfortably from 6 months until teenage years. The Tripp Trapp highchair meets and complies with all international safety standards. Provides parents with the reassurance and peace of mind that their child is not only safe but also secure in the Tripp Trapp highchair.

Tripp Trapp is fitted with a height-adjustable seat plate. Elevates children to the correct height whilst seated, with elbows comfortably resting at table height. Tripp Trapp provides the ideal position for eating, playing and socialising around the family dinner table. 

The ability to adjust and raise Tripp Trapp to the correct elevated position at the table makes it easy for parents and their child to reach food, toys and utensils. Reduces strain for everyone. Tripp Trapp is made from strong and resilient beech wood, which contributes to higher safety.

Tripp Trapp only requires the umbraco key to assemble and adjust. Enables easy assembly, disassembly, and chair adjustment as the child grows. Protects Tripp Trapp with a high-quality coating. Provides a smooth and resistant surface. Tripp Trapp's protective coating reduces scratches and makes the highchair easier to clean and maintain.

The absence of a tray makes it possible to bring the Tripp Trapp into the table. Bringing the child to the table enhances communication between parents and kids.

Please note: this is the latest edition, so pre-2011 / 2012 accessories will not fit this chair.

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SKU: 71115986270

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4.2 ★★★★★
Based on 25 reviews
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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
Grantham, 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
Lowell, 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
Port Orchard, 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
Boise, 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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