SKU: 42414292983
uppababy mesa max discontinued

uppababy mesa max discontinued UPPAbaby Mesa Max Infant Car Seat

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Description

uppababy mesa max discontinued UPPAbaby Mesa Max Infant Car SeatThe UPPAbaby MESA MAX is the extended capacity version of the MESA series, covering babies from 4 to 35 lbs compared to the standard MESA's 30 lb limit. That additional five pounds of capacity is meaningful for larger babies who outgrow a standard infant seat before they are developmentally ready for a convertible car seat, giving parents more time in the rear facing infant seat stage without needing to transition early. Like the rest of the MESA

The UPPAbaby MESA MAX is the extended-capacity version of the MESA series, covering babies from 4 to 35 lbs compared to the standard MESA's 30 lb limit. That additional five pounds of capacity is meaningful for larger babies who outgrow a standard infant seat before they are developmentally ready for a convertible car seat, giving parents more time in the rear-facing infant seat stage without needing to transition early. Like the rest of the MESA lineup it fits directly onto the Vista V3 and Cruz V3 without adapters, and onto the Minu V3 and Ridge with adapters sold separately.

The MESA MAX base includes both a load leg and an Anti-Rebound+ Panel, which is the most comprehensive base safety configuration in the MESA lineup. The load leg extends to contact the vehicle floor and reduces forward seat rotation during a frontal crash, limiting the head excursion that causes the most serious infant injuries. The Anti-Rebound+ Panel limits seat rotation during rebound after a frontal crash and provides additional protection in rear-impact collisions. The SmartSecure system uses a red-to-green visual indicator to confirm correct installation without guesswork, and auto-retracting LATCH stores the connectors automatically. Bubble level indicators on both sides of the base and a four-position adjustable foot ensure correct recline angle across different vehicle seat contours.

The carrier weighs 9.9 lbs without the canopy and insert. The no-rethread five-point harness adjusts height simultaneously with the infinite-position headrest, which means harness position stays correct as the baby grows without separate readjustment steps. The extra-large UPF 25+ hideaway canopy provides 43% more coverage than previous MESA models and tucks away neatly when not in use. The carrier shell includes side ventilation panels for airflow during warmer weather. The belt routing system allows secure baseless installation using the vehicle seat belt for rideshare and travel, and the seat is FAA certified for aircraft use.

All fabrics are DualTech and PureTech fire retardant free, GREENGUARD Gold Certified, and machine washable. The robust infant insert supports correct positioning for babies from 4 to 11 lbs during the newborn stage. ANB Baby carries the full UPPAbaby collection including the MESA V3 if you are comparing current models, and all orders over $45 ship free.

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SKU: 42414292983

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4.8 ★★★★★
Based on 18 reviews
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William P Ross
Phoenix, 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
Fort Morgan, 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
Charlottesville, 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
Lexington, 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.
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Reviewed in the United States on May 15, 2018
S
Verified Purchase
Stergios Papadimitriou
Massapequa, 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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