SKU: 90451808952
veer gear double stroller

veer gear double stroller Veer All-Terrain Cruiser XL Wagon

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Description

veer gear double stroller Veer All-Terrain Cruiser XL WagonThis unique design pushes, turns and pivots just like a stroller and pulls just like a wagon. Its adaptable to any rugged outdoor terrain (including sand, snow and gravel) and its amazingly easy to maneuver when fully loaded. You can attach your infant car seat (adapters available for just about any brand, sold separately), so the cruiser works for infants, toddlers and young kids alike. It comes with 3 point safety harnesses for two riders (up to 55

This unique design pushes, turns and pivots just like a stroller and pulls just like a wagon. It’s adaptable to any rugged outdoor terrain (including sand, snow and gravel) and it’s amazingly easy to maneuver when fully loaded.

You can attach your infant car seat (adapters available for just about any brand, sold separately), so the cruiser works for infants, toddlers and young kids alike.

It comes with 3-point safety harnesses for two riders (up to 55 lbs each), and there’s also a nap system accessory sold separately that transforms the Cruiser into a cozy bassinet.

Kids love the comfy open-air ride with plenty of things to keep them happy, like two cup holders, a drink and snack tray, six mesh interior pockets and an expandable footwell. The contoured and vented seats are extra comfy, too.

The Cruiser has front wheel suspension, large rugged tires and a one-touch footbrake. It’s made of lightweight aircraft-grade aluminum with a single-frame patented wall system that eliminates finger pinches. Extra safe and stable, it’s even certified as a stroller by JPMA and meets or exceeds stroller safety standards around the globe.

When you’re done with your outing, the Cruiser folds flat for easy in and out of small trunks, and stands upright for storage.

Details:

  • Holds two riders up to 55 lbs each
  • Birth through 5 years
  • Works well on any terrain, including sand and snow
  • Safe and stable design
  • Dimensions: Body Open: 37” L x 20” W x 23” H, Body Folded: 37” L x 20” W x 14” H
  • Body Folded (wheels removed): 37” L x 20” W x 9” H
  • Wheelbase: 24” W
  • Capacity: Passenger capacity: 55 lbs per seat x 2 seats
  • Cargo-only or pet weight capacity: 250 lbs
  • Cruiser weight: 32.6 lbs (with wheels), 24.6 lbs (wheels removed)
  • All terrain performance
  • Traditional stroller push steering
  • Wagon pull mode for uneven and soft terrain
  • 2 seats with 3-point harness
  • Compact fold
  • Performance handle grip
  • Adjustable handle height
  • Expandable footwell
  • Front suspension
  • Robotically welded aluminum frame
  • Large rugged, knobby, polyurethane foam tires
  • Rear wheel fenders
  • Contoured and vented seats
  • Durable water and stain-resistant fabric sidewalls
  • Easy removable wheels
  • One-touch foot brake
  • Hose cleanable
  • Compatible with select infant car seats from Graco, Britax Legacy (pre-2024 models), UPPAbaby,
  • Nuna Maxi-Cosi, Cybex, Clek, Britax, Chicco, Peg Perego)
  • Meet all ASTM stroller safety standards; JPMA certified
  • Two-year warranty

Returns/Exchanges:

  • All car seats, strollers, furniture and gear items must be sealed and in original packaging to be eligible for a return or exchange. These products are covered by a manufacturer's warranty.
Shipping Notes
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Exchange/Return Notes
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SKU: 90451808952

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Amazon Customer
Draper, US
★★★★★ 4
Just learning it
Format: Paperback
Nice learning book just have to finish it
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Reviewed in the United States on December 10, 2025
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Kindle Customer
West Palm Beach, US
★★★★★ 5
Very useful book
Format: Paperback
I use it for the machine learning class I teach.
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Reviewed in the United States on May 3, 2026
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Tommy Jonsson
Battle Creek, US
★★★★★ 5
Cover many areas in detail and recommendations for more to read for what's outside
Format: Paperback
Good book!
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Reviewed in the United States on May 4, 2026
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Moses Kayanda
Massapequa, US
★★★★★ 5
One of the best machine learning books...
Format: Paperback, Format: Paperback
Machine Learning can often be intimidating whether you are starting out or already a practitioner. It is easy to get stuck on one concept, walk away frustrated, or just copy that code you find on StackOverflow without really understanding what it does. What the authors of this book, Machine Learning with PyTorch and Scikit-Learn, have managed to do is to keep the reader engaged giving a deeper illustration as to how the concepts work. In this book, you get practical code examples, a detailed explanation of how the various library tools work, and exposure to the mathematical concepts behind machine learning algorithms. In addition, what I like about the book unlike many machine learning books is that the authors have managed to intuitively explain how each algorithm works, how to use them, and the mistake you need to avoid. I have not read a Machine Learning book that better explains Transformers as this one does. The authors have managed to give a detailed dive into this model architecture through well-explained codes and illustrations. As a reader, you walk away having intuitively grasped the concepts of attention and self-attention in ways that will make this crucial NLP architecture clear. You get exposed to pre-trained models from HuggingFace library which really helps to have that hands-on experience working with large datasets. As they have done throughout the book, the authors have broken down those complex mathematical operations into simple explanations that are easy to follow. What I generally like about the book is how it seamlessly connects all the chapters, not throwing off the reader. There are numerous external resources quoted throughout the book. This helps spark that curiosity to dig deeper. In addition, you get introduced to PyTorch, getting exposed to all those sophisticated libraries that help the reader learn how to maximize their compute power. I would say it is not intimidating at all even if you have not used PyTorch before. I would recommend this book to anybody seeking a textbook that is both easy to read and modern in its content. If were to rate the book I will give it a 10/10 as it really applies to both beginners and experienced practitioners, covers all the concepts one needs to apply in their operations, and acts as a quick reference.
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Reviewed in the United States on March 1, 2022
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Gabe Rigall
Cuba, US
★★★★★ 5
Thorough Primer for Machine Learning and PyTorch
Format: Paperback
BLUF: A thorough primer for machine learning enthusiasts with plenty of theory to underscore its many practical examples. A definite must-have for anyone looking to add PyTorch to their machine learning tool belt. PROS: - Extremely thorough (if not comprehensive). I really appreciate that this book doesn't just thrust one into building models with PyTorch. It starts at the "beginning" and provides examples, theory, additional resources, and citations along the way. - Theory. Those whose calculus and linear algebra courses ended many years ago will appreciate (if not remember exactly) the mathematical theory and notation that accompanies almost every paragraph. This book gives one the opportunity to "dig deeper" or stay in the shallows until the notation stops. - Python. Rather than simply utilizing Scikit-Learn to illustrate concepts and introduce models, this book contains many sections where models (such as a Perceptron) are coded from the ground up so the reader can fully understand the underlying mechanics. Python enthusiasts will nerd out. Parents of small children might want to skip a few pages. - Graphs, charts, and graphics. There are plenty of places where a drier text might have foregone the use of graphs. This text does not. It does however refrain from overusing them. - PyTorch. This should be obvious from the title, but this text prioritizes PyTorch instead of TensorFlow. This is especially helpful for those looking for an alternative to Keras and TensorFlow as the PyTorch API is very user-friendly. CONS: - Almost too much code. This isn't a true "con" but anyone wanting to emulate or follow along with the examples would do well to get the digital edition so they can copy and paste. - Length and complexity. Anyone hoping for a "quick read" or a "quick start guide" will be disappointed. This book hovers somewhere between an undergraduate primer and a graduate-level text for length and readability. This is not to say that it's difficult to read, merely that there are other "quick start" / "practical" texts out there that cater more to a lay audience.
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Reviewed in the United States on February 26, 2022

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