SKU: 4080097016
uppababy mesa max height

uppababy mesa max height UPPAbaby MESA Infant Car Seat Online

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Description

uppababy mesa max height UPPAbaby MESA Infant Car Seat OnlineFeatures of UPPAbaby Mesa Infant Car Seat The UPPAbaby Mesa Infant Car Seat is a parent favorite. Quick glance features: Families love the UPPAbaby Mesa Infant Car Seat! The Mesa Infant car seat meets or exceeds all crash test standards, and looks great doing it. UPPAbabys SecureLatch system makes it easy for parents to properly install the seat and keep baby secure. Features of the UPPAbaby Mesa Infant Car Seat: The UPPAbaby Mesa Infant car seat, the

Features of UPPAbaby Mesa Infant Car Seat

The UPPAbaby Mesa Infant Car Seat is a parent-favorite. Quick glance features:

Families love the UPPAbaby Mesa Infant Car Seat!


The Mesa Infant car seat meets or exceeds all crash test standards, and looks great doing it. UPPAbaby’s SecureLatch system makes it easy for parents to properly install the seat and keep baby secure.

Features of the UPPAbaby Mesa Infant Car Seat:

The UPPAbaby Mesa Infant car seat, the sleek and safe seat you love, features:

  • SmartSecure base for a 10-second install
  • Side impact protection
  • Soft, premium fabrics keep baby comfy
  • Removable and washable seat fabric
  • Lightweight carry gives your back a break
  • Adjustable headrest with no-rethread harness
  • SPF 50+ hideaway canopy
  • Low-profile base
  • 4-position adjustable foot for easy leveling
  • Attaches to the Vista and Cruz stroller with no adapters needed.

SmartSecure base for a 10-second install

The Mesa car seat is the only infant seat with the innovative 10-second SmartSecure install system. SmartSecure uses a combination of a tightness indicator and self-retracting latch connection for fast and easy insulation. Just watch the indicator window change from red to green, to get confirmation that the seat is installed properly. This system helped earn the Mesa a NHSTA 5-star rating.

Side impact protection

The adjustable headrest on the Mesa gets serious reinforcement with EPP foam. It’s comfy for baby, but also provides extra protection for side impact collisions. This simple feature helped the Mesa perform four times better than other premium infant car seats in crash tests.

Premium fabrics keep baby comfy

The updated fabric for UPPAbaby MESA Infant Car Seat is both breathable and moisture-wicking. That means your little bundle of joy will stay comfy and cool, no matter what the weather. The Henry (Blue Marl) and Jordan (Charcoal Melange) versions are made from naturally fire-resistant wool!

Removable and washable seat fabric

Spit ups and spills are a part of life with infant, but with the Mesa car seat that’s no big deal. Just remove the seat’s fabric portion and throw it in the washing machine. Lay flat to dry and reattach.

Lightweight carry gives your back a break

The Mesa carrier weighs in at 9.9 pounds. That means your back will get a break!

Adjustable headrest with no-rethread harness

If you’ve ever had to rethread the straps on a car seat or stroller, you know what a pain it is. With the Mesa infant car seat, the adjustable headrest doesn’t require any of that hassle! It grows with your baby with ease.

SPF 50+ hideaway canopy

The hideaway canopy provides ample sun coverage for infants. When stowed away, it won’t get in your way or be a bother in the car. It’s the perfect flexibility for strolling, when you pair the Mesa with your favorite stroller.

Low-profile base

The slim and low-profile Mesa base won’t take up your whole backseat. If you have multiple children riding with you, the Mesa seat is the perfect choice for your infant.

4-position adjustable foot for easy leveling

No matter how your seat slants, the 4-position design of the base will make sure your car seat is installed properly for baby’s safety.

Attaches to the Vista and Cruz stroller with no adapters needed

Use the Mesa with your favorite stroller! It fits the Vista and Cruz without an adapter and can be adapted to many other premium strollers too.

Do you need an adapter to use the Mesa on the UPPAbaby Cruz or UPPAbaby Vista stroller?

The Mesa car seat fits directly on the Cruz and Vista stroller, without an adapter.

What is the difference between the 2015 UPPAbaby Mesa car seat and the 2017 / 2018 / 2019 Mesa car seat?

In 2017 / 2018 / 2019 UPPAbaby made a few updates to the Mesa.

  • New Colors: In 2018, UPPAbaby added the Jordan (Charcoal Melange) and reintroduced the Denny (Red) fabric choices.  In 2019, UPPAbaby added the Bryce fabric choice.
  • Chemical Free Fabric: The Jordan Mesa and Henry Mesa are both made from a naturally fire-resistant wool, reducing your baby's exposure to flame-retardant chemicals.
  • Softer Fabric & Additional Padding: New fabrics are softer and additional padding makes the Mesa an even more comfortable ride for baby.
  • Sleeker, More Tailored Look: The use of laminated foam and the redesigned seat liner, result in a sleeker, more-tailored look.
  • New Travel Bag: UPPAbaby is introducing a new travel bag, sold separately.

What is the weight limit of the Mesa car seat?

The Mesa is rated from 4 to 35 pounds, and up to 32 inches in height, whichever comes first.

Is the UPPAbaby Mesa a safe car seat?

The UPPAbaby Mesa car seat meets or exceeds all ASTM and JPMA compliance standards and governmental safety and testing standards. State and federal safety standards also require all car seats to meet strict flame retardancy standards. Some manufacturers use toxic brominated and chlorinated chemicals to meet flame retardancy, but UPPAbaby car seats meet all applicable flame retardancy standards without these potentially harmful chemicals.

Does the UPPAbaby Mesa Infant Car Seat come with a base?

When you purchase the Mesa car seat from an UPPABaby dealer, it includes one car seat base as well.

Does the UPPAbaby Mesa car seat have an expiration date?

So long as the Mesa is never involved in a car accident, it can be used for 7 years after the date of manufacture.

How long is the UPPAbaby Mesa when installed in the car?

When installed on its base, the Mesa measures 28 inches long.

What is the warranty on the UPPAbaby MESA Infant Car Seat?

UPPAbaby is offering an extended 36-month warranty when you register your car seat online within 3 months of purchase.

UPPAbaby Mesa Infant Car Seat Measurements and Specifications

Child Weight (lbs) Rear facing, 4 - 35 lbs (included infant insert recommended for babies 4 - 8 lbs)
Child Standing Height (in) 32" or less
Product Dimensions (in)

Infant Car Seat:  17"(w) x 25.8"(l) x 23"(h)

Seat with base:  17"(w) x 28"(l) x 25"(h)

Base:  14.5"(w) x 21.3"(l) x 13"(h)
Product Weight (lbs)

9.9 lbs (Carrier), 9 lbs (Base)
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SKU: 4080097016

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4.8 ★★★★★
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Kirsten
Massapequa, US
★★★★★ 5
Holds a decent amount of jewelry!
Color: Carbonized Brown, Color: Carbonized Brown
I was quite impressed with this little jewelry box. Although it is on the smaller side, it utilizes every bit of the storage space available really well. I’d ultimately love to get a bigger armoire- as it is, this jewelry box contains what I wear most often, but I have a larger collection than this particular jewelry box can hold- my plan is to find a larger jewelry armoire that resembles what my mother had because I loved that one and then passed this one down to my daughter who loves it. For its size, it does absolutely hold a lot. I definitely underestimated how much it would hold. I love that there are drawers and well. I would love to see the ring area hinged so that I don’t have to reposition it when I’m done grabbing my rings, I think it’s a really cool, unique way to approach that particular area. I love that every little bit at this jewelry box is designed to have utility. I hate wasting space and time and I love good organization so it’s been really nice being able to pack as much as I can in there. The top opens up to space for earrings and other miscellaneous items. There are both open and more structured components. And the space for bracelets rotates, which is really nice- I didn’t realize that it rotated and I was a little bit worried that I was gonna constantly knock things down while I was reaching through or something. There is lots of room inside both doors for necklaces, and it fits a lot more than I thought it would. The wood stain is a really pretty kind of ashy natural stain- the sort of grey tint is really nice and it’s gorgeous. I’m not a huge fan of mirrors as far as the front goes, but I do have an artist in house who is really good at coming up with stuff for this, just a little ways to put art in your every day, so I’ll probably have her paint over. The jewelry box also doesn’t take much space up at all. While I am looking for something with a little bit larger footprint, I don’t necessarily want to waste a bunch of real estate in the meantime so I’m really pleased with how compact it is. This is a great little jewelry box - as I mentioned it doesn’t house all of my jewelry, but that’s because my collection is mostly heirloom and I don’t want to take it out from where it is right now. If it were larger, I would probably do so but for now it just houses my everyday items and a little bit extra. I think it’s great and I’m super happy with it!
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Reviewed in the United States on March 17, 2026
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Alexandria, US
★★★★★ 5
Excellent book, possibly currently unique in coverage of latest ideas
This book is possibly currently unique in its coverage of the latest ideas in the field of deep learning -- and it is a very convenient and good survey of fundamental concepts (linear algebra, optimization, performance metrics, activation function types), different network types (multi-layer perceptron, convolutional neural networks, and recurrent neural networks), practical considerations (data set, training and validation, implementation), and applications (comments on existing real-world/commercial uses). The final 235 pages of the content portion of the book is dedicated to topics in "Deep Learning Research", and these topics are truly at the current frontier. Another reviewer said that one could gain the same knowledge of cutting-edge research by reading all of the latest papers (from academia and industry), but the "research" section of this book offers the following: Selection of the most notable research by the very experienced authors of the book, and collection of similar research in to a broader discussion of themes, and the additional insights. The book covers very advanced and new ideas currently being explored, and it is very nice to be able to have a consistent and coherent presentation of all of those ideas. However, the book is also packed with valuable observations and pointers about more basic aspects of deep learning implementations and practices -- and such commentary is in depth and includes substantial analysis and mathematical derivation (in an intuitive presentation that often includes graphs illustrating the phenomenon). As someone with an intermediate level of knowledge and experience of neural networks, I am really grateful for this book, because seems like the ideal resource for learning cutting-edge ideas and practices, with context. The book has excellent scope and depth, and I am confident that anyone with a solid background in linear algebra, calculus, statistics, and general machine learning, and basic neural networks (multi-layer perceptrons) will find this book to be very exciting and perhaps unique in its ability to take the reader to the next level and a new frontier. I was personally excited to learn about the idea of representing the dependencies of intermediate quantities by directed graphs, and how this can be used to perform calculations for recurrent neural networks efficiently. And I think the long chapter on recurrent neural networks is very helpful. Having said all of this, I think only people with significant working knowledge and experience with neural networks and mathematics -- people whose academic or professional focus has been neural networks for at least a year or two -- would benefit from this book. This book answers a lot of the deeper questions that one is likely to have while developing a solid understanding of the fundamentals, and that's one of the book's tremendous values, but this book assumes an understanding of the fundamentals (but does briskly cover the basics). I think this book is a perfect follow-up book for the excellent book "Neural Network Design (2nd edition)" by Hagan, Demuth, Beale, and de Jesus, and I highly recommend the latter for gaining the solid background needed to have a thrilling experience with the "Deep Learning" book. In summary, I am very glad this "Deep Learning" book was written, and I think the "Deep Learning" book will be a great benefit to a lot of people, and to the evolution of the field.
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Reviewed in the United States on April 18, 2017
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Zygerian99
Natrona Heights, US
★★★★★ 5
The definitive guide to becoming a researcher in the field
Format: Hardcover
This is not a coding book. I see a lot of negative reviews around the expectation that this book would teach the reader how to quickly build machine learning systems and write code. This book is not for that audience. If you just want to build applications, don't worry about how deep learning works. It's akin to needing to understand how an engine works just to drive a car. If you are looking for a coding resource, try: https://www.amazon.com/Hands-Machine-Learning-Scikit-Learn-TensorFlow/dp/1492032646/ref=sr_1_4?keywords=machine+learning+tensorflow&qid=1579608765&sr=8-4 . And even with that book, the material still goes far beyond what you need - use it as a light reference. I bought this book as an aspiring machine learning researcher, and towards that end, it is the best resource available in print (still true as of 2020). For instance: The first 5 chapters are timeless. These are things that were mostly established 20 or 30 years ago and beyond and are mostly STEM fundamentals at this point. There are whole textbooks dedicated to each of those chapters, but the authors provide a quick refresher and overview of probably 80% of what you'll encounter in deep learning. If you haven't previously learned each of these subtopics, you'll probably want to study them individually since they are the key to innovating (linear algebra, probability & stats, numerical computation, machine learning fundamentals). Chapters 6 thru 9 are the foundation of deep learning. We're about 12 years into seeing rapid change in the deep learning space, yet all of these principles and techniques still hold (many recent innovations are still relying on Convolutional models in 2020, which is the most layered/complex topics in those chapters). Therefore, I'd wager that these chapters are also fairly stable knowledge that is worth internalizing if you want to be deeply involved in the future of machine learning. Chapters after 9 are mostly experimental topics, and many of them are already the wrong strategies for optimal results. But there are interesting ideas in here that you'll often encounter in the wild, so it's good exposure to various topics. But probably not worth much of your time. And lastly, there is good history in here from people who know the space intimately. It's a good way to piece together the developments and learn the lexicon of deep learning so you can have intelligent conversation with experts.
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Reviewed in the United States on January 21, 2020
S
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Shannon
West Palm Beach, US
★★★★★ 5
The best DL/ML book I have ever seen!!
Format: Hardcover
Fantastic deep-learning book! The logic is very easy to follow, but the content is very thorough when it comes to explaining the theories behind it, making it perfect for beginners as well as math and CS students. The best DL/ML book I have ever seen!!
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Reviewed in the United States on November 30, 2025
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William P Ross
Pawtucket, 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.
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Reviewed in the United States on March 15, 2017

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