SKU: 63469585324
britax stroller extension

britax stroller extension Britax Phases Travel System

Sale price$23.20 Regular price$25.78
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Description

britax stroller extension Britax Phases Travel SystemGrow together from day one with the Phases travel system. This infant car seat and stroller combo features 6 ways to ride including pramette mode plus a convenient parent organizer. You cant wait to welcome your little one into the world, but preparing for their arrival can be overwhelming. There are so many things youll need to have on hand and so many options to choose from. As you check each item off your list, you can rest easy knowing that with

Grow together from day one with the Phases™ travel system. This infant car seat and stroller combo features 6 ways to ride — including pramette mode — plus a convenient parent organizer.

You can’t wait to welcome your little one into the world, but preparing for their arrival can be overwhelming. There are so many things you’ll need to have on hand — and so many options to choose from. As you check each item off your list, you can rest easy knowing that with the Phases™ travel system, you’ll be all set for effortless outings with your baby from day one. Designed for convenience, comfort, and versatility, this car seat and stroller combo includes the Phases stroller, the Arbor™ infant car seat, and the StayTight™ car seat base, plus a parent organizer, a stroller bumper bar, and a child tray. The Phases stroller is designed to adapt to your child's needs as they grow, starting with infant car seat mode for newborns and easily transitioning to pramette mode or toddler mode when your child is ready. And, thanks to the DuoConnect™ system, you can go from car rides to strolls without keeping track of adapters — just click and keep moving. When the time comes to install the car seat in your vehicle, you can breathe a sigh of relief knowing that the StayTight™ base is designed to take care of the hard part for you. For those on-the-go moments when your hands are full, the stroller organizer helps you keep everything you need within reach — because you’ve got enough to juggle. With an adaptable stroller, a comfortable and easy-to-install car seat, and convenient accessories, this all-in-one box system helps take the stress out of those early car rides and outings, giving you and your little one everything you need to grow together from day one.

Features

One System. One Box. From Day One.​

Includes the Phases™ stroller, the Arbor™ infant car seat, and the StayTight™ car seat base, plus a parent organizer, a bumper bar, and a child tray.

6 Ways to Ride

Options for forward-facing and parent-facing infant car seat mode and toddler mode. Plus, the stroller easily converts into pramette mode (forward-facing or parent-facing).

StayTight Installation​

Car seat setup is a cinch thanks to the StayTight base, which includes a built-in seat belt tensioner and an automatic lock-off.

DuoConnect™ System​

Effortlessly transition from car rides to strolls. No adapters needed!​

Parent Organizer​

With multiple pockets and two large cup holders.​

Light to Lift, Quick to Fold

Lightweight car seat and stroller frame + one-hand, one-step stroller fold. ​

ReboundReduce™ Carry Handle

Carry handle helps provide stability when used in the upright position. ​

UPF 50+ Canopy​

Help protect your tiny passenger from the sun with the large UPF 50+ canopy and visor. ​

Base-Free Stability

Extra belt path on the back of the seat helps keep it stable when installing without the base.

Child Tray

With dishwasher-safe drink & snack holders.​

Large Storage Basket​

Easy to access with plenty of room for your must-haves.

Specifications

  • Product Weight (Car Seat Only): 9.9 lbs
  • Seat Back Compartment Height: 18"
  • Harness Slot Heights: 5.5" / 7.5" / 9.5" / 11.5"
  • Buckle Strap Depths: 2.5" / 5.5"
  • Child Weight(Car Seat Only): 4-30 lbs / (Stroller Only) Up to 50 lbs
  • Rear-facing Harnessed Height: Less than 32"
  • Product Weight (Base Only): 7.4 lbs
  • Stroller Product Weight: 19.6 lbs
  • Maximum Unfolded Dimensions: 36"L x 23"W x 45.5"H
  • Folded Dimensions, Wheels On: 22.5”L x 23”W x 39.75”H
  • Stroller Product Length/Depth: 36"
  • Stroller Product Height: 45.5"
  • Stroller Product Width: 23"
  • Seat Area Depth/Width: 12" / 8.25"
  • Shoulder Width: 7.75"
Shipping Notes
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Exchange/Return Notes
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SKU: 63469585324

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Walter Echo-Hawk, author of THE SEA OF GRASS.
Natrona Heights, 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
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Verified Purchase
Par
New York, 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
R
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Richard Hackathorn
Waukegan, 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
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Verified Purchase
Amazon Customer
Lake Worth, 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
Massapequa, 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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