SKU: 2928434250
indigo uppababy

indigo uppababy Bugaboo Donkey 6 Duo Complete Stroller Bundle

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Description

indigo uppababy Bugaboo Donkey 6 Duo Complete Stroller BundleThe go anywhere convertible stroller that truly carries it all. The Bugaboo Donkey 6 Duo Complete is built to grow with your family, from single to double, while offering unmatched storage and smooth handling across any terrain. Large puncture proof wheels and a tight turning radius make it easy to steer one handed, even when fully loaded with kids and groceries. Despite its impressive capacity, the Donkey 6 keeps a slim profile at just 23. 6 inches

The go anywhere convertible stroller that truly carries it all. The Bugaboo Donkey 6 Duo Complete is built to grow with your family, from single to double, while offering unmatched storage and smooth handling across any terrain.

Large puncture proof wheels and a tight turning radius make it easy to steer one handed, even when fully loaded with kids and groceries. Despite its impressive capacity, the Donkey 6 keeps a slim profile at just 23.6 inches wide in single mode, as narrow as a typical full size stroller. In double mode, it measures 29.1 inches and still fits through standard doorways.

Storage is where it truly shines. The underseat basket is now 50 percent larger, holding up to 33 pounds or 70 liters. The redesigned side luggage basket doubles as a changing bag, keeping essentials within reach. In single mode, it carries up to 22 pounds on the chassis. In double mode, it secures to the handlebar and holds up to 8.8 pounds.

Crafted for superior comfort, the Donkey 6 also introduces a new standard in textile dyeing. Its innovative dope dyed fabrics use no water and require less energy and fewer chemicals during production. The result is long lasting color that resists sunlight and washing, with pigment built directly into the fiber for enhanced durability and a more eco conscious finish.

New textile dyeing introduced on: Heritage Black, Deep Indigo, Fern Green and Cocoa Brown

Features:

  • For use from birth with the bassinet and up to 50lbs in each stroller seat
  • Easily converts from a single stroller to a side - by- side double stroller in just three clicks
  • For use with one child (Single), two children of different ages (Double), or twins (Twin)
  • Extra - large sun canopy complete with a quiet peek - a- boo/breezy window
  • Standing, one - piece fold in any configuration with bassinet and/or seat(s) attached
  • Fits through standard doorways in Single, Double, and Twin mode
  • Easy to push, turn and maneuver with just one hand on any terrain
  • One - hand reclining seat; 3 positions parent facing & 2 positions front facing

New for Donkey 6:

  • Newborn bassinet(s) with twice as large breezy panels, soft organic cotton lining and extended apron with pocket
  • Under seat basket with 50% more storage space holding up to 33lb
  • Redesigned side bag doubles as a changing bag and can attach to the handlebar holds up to 8.8lbs (while in double on handlebar)
  • Seat fabric covering footrest for cleaner look, back seat pocket and color matching harness with longer straps
  • Lighter wheel design
  • Durable recycled fabrics and premium branding

Specifications:

  • Max Child Weight lbs.: 50 lbs.

Dimensions

  • Single (seat): 34.2" x 23.6" x 43.7"

  • Double (bassinet): 36.2" x 29.1" x 43.7"

  • Folded (2 piece): 35.04" x 23.62" x 13.78"

  • Folded (1 piece): 22" x 24.2" x 35.4"

Weight

  • Single (seat): 33.7 lbs

  • Single (bassinet): 35.9 lbs

  • Double (bassinet + seat): 42.1 lbs

Warranty

  • 2 year warranty

  • Extended to 4 years with product registration

What's Included:

Your complete Bugaboo Donkey 6 Duo Complete stroller comes ready for the road ahead and includes:

  • 1 Stroller Base
    Chassis with pre assembled grips, wheels, and wheel caps
  • 2 Seats
    Two complete seat sets including seat hardware, footrests, seat fabrics, carry handles, leather look grips, and five point safety harnesses
  • 1 Bassinet
    Bassinet hardware and fabric with breezy panel for airflow and visibility, plus aerated mattress
  • 1 PureBreeze™ Mattress
    Dual sided with enhanced breathability for year round comfort
  • 2 Sun Canopies
    Two full canopy sets with wires and clamps, UPF 50+ protection, and peek a boo panels
  • Side Luggage Basket + Underseat Basket
    The side basket allows you to switch back to Mono mode whenever needed.
Shipping Notes
  • Free Standard Shipping on $100+ Orders to the USA.
  • Except Preorder products are shipped in 48 hours.
  • Delivery to the USA:
  1. Standard Shipping : 3-10 business days
  • If time is of the essence, please consider selecting expedited delivery for faster service.
Exchange/Return Notes
  • We offer a 30-day return/exchange service after receiving.
  • Final sale items are not eligible for returns or exchanges.
  • To process your return/exchange, please contact us at [email protected]
  • Please click here for more details>>> Return & Exchange Policy
SKU: 2928434250

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Verified Purchase
Richard Hackathorn
Grantham, 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.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on February 26, 2022
A
Verified Purchase
Amazon Customer
Whiting, 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
Belleville, 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
T
Verified Purchase
Tommy Jonsson
Los Angeles, US
★★★★★ 5
Cover many areas in detail and recommendations for more to read for what's outside
Format: Paperback
Good book!
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 4, 2026
M
Verified Purchase
Moses Kayanda
San Leandro, 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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