SKU: 11610454581
is nuna compatible with uppababy

is nuna compatible with uppababy UPPAbaby Vista V3 Twin Stroller + Nuna PIPA Series Travel System

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Description

is nuna compatible with uppababy UPPAbaby Vista V3 Twin Stroller + Nuna PIPA Series Travel SystemMake your own travel system with the Vista V3 Twin Stroller + Nuna PIPA Series Travel System by UPPAbaby and be prepared for any adventure with your little ones. Simply choose the color of your stroller and your PIPA seat, and you are ready to roll! This bundle comes with everything you need no additional adapters required! This bundle is created to make choosing your ideal travel system a breeze while featuring baby safe materials, ensuring your

Make your own travel system with the Vista V3 Twin Stroller + Nuna PIPA Series Travel System by UPPAbaby and be prepared for any adventure with your little ones. Simply choose the color of your stroller and your PIPA seat, and you are ready to roll! This bundle comes with everything you need - no additional adapters required!

This bundle is created to make choosing your ideal travel system a breeze while featuring baby-safe materials, ensuring your little ones don't come in contact with any nasty chemicals. The Vista V3 Twin Stroller + Nuna PIPA Series Travel System by UPPAbaby helps you be worry-free and helps you on the road of parenthood.

UPPAbaby's Vista V3 Twin Stroller features mesh All-Weather Comfort Seats that keep the kiddos cool in warmer months, with removable padded Seasonal Seat Liners for added warmth when the temperature drops. The seats also feature extendable, water-repellent UPF 50+ canopies and easy-to-peek windows, offering airflow and protection from the sun rays while allowing you to keep an eye on your little ones. The easy-to-adjust no-rethread harness with a magnetic buckle keeps each child safe and allows you to secure them in with one hand. The seats can be reclined with one hand for on-the-go naps, and the adjustable footrests ensure proper positioning of your little ones' legs as they grow. Both seats are designed to be reversible, so the kids can face you for comfort and bonding time, or face the world when they become curious about their surroundings.

The UPPAbaby Vista V3 Twin Stroller features an enhanced FlexRide suspension that provides a smooth stroll on any terrain, even with multiple kiddos on board. The one-step self-standing compact fold with the seat attached makes travelling and storage a breeze. The extra-large basket is easy to access from all sides and provides ample storage for your day-to-day necessities on the go. The one-hand handlebar, finished with full-grain REACH-certified leather, is easily adjustable to accommodate different parent heights. Thanks to reflective details on the wheels and the basket, the Vista V3 is visible at all times of day, providing added safety while strolling.

Add the UPPAbaby Bassinets V3 (sold separately) for a comfortable ride from day one!

Vista V3 Specifications:

  • Toddler seat and RumbleSeat are GREENGUARD Gold-certified for healthier air quality and low chemical emissions
  • Unfolded dimensions (with one seat): 36" L x 25.7" W x 39.5" H
    Folded dimensions: 17.3" L x 25.7" W x 33.3" H with one seat, 13" L x 25.7" W x 32" H frame only
  • Stroller wheels: 8.1" front, 11.3" rear
  • Weight: frame + two seats 35.4 lbs; frame 20 lbs, toddler seat 7 lbs, Rumbleseat 8.4 lbs
  • Stroller suitable for use from birth (with car seat or additional bassinet) or from 3 months, up to 50 lbs on the toddler seat or 40 lbs on the Rumbleseat
  • Basket capacity: 30 lbs

Nuna PIPA Series combines the industry's highest standards with low chemical emissions to bring a line of car seats that are not only incredibly safe to ride in but also completely non-toxic and safe for the baby's health. All PIPA Series car seats are GREENGUARD Gold certified for low chemical emissions and are made of materials that are naturally fire resistant, without the use of chemical fire retardants. All PIPAs come with a base as well as a removable infant insert for use from birth. Not sure which PIPA is the right one for you? Click here for a comparison chart!

What's included:

  • UPPAbaby Vista V3 Stroller
  • UPPAbaby V3 Rumbleseat, with adapters
  • UPPAbaby Upper Adapters
  • 2x Nuna PIPA Series Car Seat With Infant Inserts and Bases
  • 2x Nuna Pipa Ring Adapters for UPPAbaby Vista + Cruz

Shipping Notes
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SKU: 11610454581

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Walter Echo-Hawk, author of THE SEA OF GRASS.
Port Orchard, US
★★★★★ 5
Native American history at its best!
Format: Hardcover
Kent Blansett's engrossing story about the life & times of the famed Mohawk activist Richard Oakes is Native American history at its best. I appreciated the well-written context provided about the birth, growth and impact of the Red Power Movement and the pivotal role that social justice activism played in the rise of modern Indian nations in the United States today. This scholarly work helps us understand modern Native America and is a "must-read" for every Native American Studies student and scholar, as well as readers interested in important American social justice movements.
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Reviewed in the United States on April 1, 2019
P
Verified Purchase
Par
Battle Creek, US
★★★★★ 5
Excellent book on ML
Format: Paperback
This is a great book on machine learning. Topics covered are extensive - from beginner level to advanced topics including math behind different algorithms. However, not "all" algorithms are covered. Please go through the table of contents. The first part - 11 chapters - covers machine learning concepts and second part covers advanced topics with Pytorch. There are lots of excellent code and they work!! The quality of the book I received is excellent. I have gone through all 742 pages, and it has held up very well!! I used Jupyter notebook to run all examples. I created a new notebook and copied and pasted the code and ran them. This approach worked very well for me. At the same time, I could experiment with my take on the code snippets and definitely added to my knowledge. Only issue I have is on the second part of the book discussing PyTorch: (1) Some packages are a bit older version: e.g., transformer 4.9.1 whereas current version is 4.48+. It took some tweaking/recoding to get the examples working. (2) There is not much discussion on why certain architecture was chosen - e.g., number of layers, is there a rule of thumb on how to improve performance by changing these parameters? Even with CUDA the code run for a long time. Therefore, experimenting with different values of parameters become too time consuming. (3) On the same note, if I can achieve test accuracy of 90%+ using logistic regression and almost the same (perhaps one or two percent better with PyTorch with IMDB movie review dataset and that two much faster why should I use PyTorch for this dataset? Obviously, PyTorch is for certain types of problems. Discussions can be included by not adding to the exhaustive (and apt) contents. Personally I was disappointed by lack of any example on time series. Must have for ML practitioner as a reference and guide.
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Reviewed in the United States on December 20, 2024
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Richard Hackathorn
Bozeman, US
★★★★★ 5
Excellent Textbook for Hands-On Learning of ML
Format: Kindle
This textbook is for the serious life-long learners of machine learning. There are at least two ways to ‘consume’ this book. For the expert in ML, this is a textbook to study as a clear comprehensive ML overview and then to dive into sections of interest or ignorance. The concepts are grounded in code examples and are well cited (with links) to sources. Further, this textbook is appropriate if you are TensorFlow-centric and want to broaden into cutting-edge ML models/tools coded in PyTorch. For a new learner to ML, this is a textbook to DO (not just READ) with hands-on and brain-engaged. If you realize that ML is a key life-long skill for your career, consider this textbook as part of a daily learning habit (10-30 min). From personal experience, my advice to the new learner is as follows… First, clone the GitHub repository, setup your Python environment, and study the textbook, while working through the notebooks. Go on tangents and break the code. Do this methodically as part of your daily learning habit, but do not hesitate to jump ahead several chapters to prepare for tomorrow’s meeting. There is enough excellent material here for a full year of ML adventures. I did a similar strategy with Raschka’s first textbook. About four years ago, I had finished Andrew Ng’s Deep Learning Specialization as a student in his first cohort. I knew the concepts well but could not do the actual application coding. I was surprised how my Python coding improved by following Raschka’s clean and elegant style. And Raschka’s code examples were meaty enough to be springboards into working applications. Several textbook editions later, what is different about this new edition? First, it moves you through scikit-Learn (a firm foundation) to PyTorch, instead of TensorFlow. PyTorch is a better stepping-stone, both conceptually and practically. With PyTorch, you will go further with less energy, while being able to convert your efforts into TensorFlow as needed. In addition, most of the cutting-edge ML/AI/DL research is in PyTorch. It is nice to read a recent arXiv paper, clone their repository, click on the Colab tutorial, and replicate their experiments, along with picking up a ton of new coding tricks & tips. I am excited to work through these PyTorch sections to hone my skills. Second, there is a clear recognition of model tracking and tuning practices. This is often a gap in other ML textbooks and courses. Once you progress beyond the simple demo examples in a lecture, you realize that the real work is experiments, more experiments, and still more experiments, so that you must understand what the model architecture and hyperparameters are doing to your dataset. There is good coverage of scikit-Learn pipeline, grid search, model performance, and the like. Third, ML/AI/DL practice is rapidly evolving. Every week new ML packages/services become available that could save much grief on your current project. What is refreshing about Raschka’s textbook series is that he constantly adding cutting-edge topics because he likes to stay current and to help us stay current. Hence, this edition contains recent ML treats as: transformers, self-supervised learning, autoencoders-to-GAN, graph neural networks, DBSCAN, t-SNE (with brief mention of UMAP), and PyTorch-Lightning.
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Reviewed in the United States on February 26, 2022
A
Verified Purchase
Amazon Customer
Los Angeles, US
★★★★★ 4
Just learning it
Format: Paperback
Nice learning book just have to finish it
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on December 10, 2025
K
Verified Purchase
Kindle Customer
Whiting, US
★★★★★ 5
Very useful book
Format: Paperback
I use it for the machine learning class I teach.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 3, 2026

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