SKU: 72330404921
infant car seat cybex

infant car seat cybex Cybex Callisto G All in One 360 Rotating Car Seat w/Canopy

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Description

infant car seat cybex Cybex Callisto G All in One 360 Rotating Car Seat w/CanopyThis Game Changer Callisto G 360 is a rotating All in One car seat with canopy and SensorSafe smart technology that grows with your child offering safety and comfort from day one. With a quick, intuitive installation that takes just seconds. The SafetyAssure Protection System provides added peace of mind and unparalleled safety. Designed to support your little one from infant to booster, its ready to keep them safe and comfortable at every stage. The

This Game Changer Callisto G 360 is a rotating All-in-One car seat with canopy and SensorSafe smart technology that grows with your child - offering safety and comfort from day one. With a quick, intuitive installation that takes just seconds. The SafetyAssure Protection System provides added peace of mind and unparalleled safety. Designed to support your little one from infant to booster, it’s ready to keep them safe and comfortable at every stage. The Callisto G 360—built for all your family’s adventures.

Installing the Callisto G 360 is effortless and secure thanks to its SafeLock system, which allows for a one-time setup in seconds. Simply fasten the tether to your vehicle’s anchor point, route the seatbelt through the belt guide, click it into place, and close the SafeLock door. With its innovative 360° rotation, the Callisto G 360 makes loading your child easy by rotating toward the car door. Additionally, it offers five different recline positions in both rear- and forward-facing orientations, ensuring optimal comfort for your little one throughout every journey.

The Callisto G 360 is built with advanced safety features to provide unmatched protection in any situation. Its Anti-Rebound Base with SecureFix360 Tether, Linear Side Impact Protection, and SensorSafe Bluetooth-enabled chest clip work together to protect your child in the event of a crash. Reinforced by a durable steel frame, the Callisto G 360 delivers exceptional crash resistance, making it a trustworthy companion on every ride.

Complimentary install by appointment with our certified technicians. 952-912-1010

Specifications:

• 3 Modes of Use: Rear-Facing, Forward-Facing, and Belt-Positioning Booster for       long-term growth from birth through elementary years  (approx. (10 years and 57")

• 12-Position Headrest & Infant Insert: Adjustable headrest with a removable, multi-stage insert for infants

• UPF50+ Canopy: Oversized, adjustable canopy offers full sun protection

• Bluetooth-Enabled Chest Clip: Sends app alerts if the child unbuckles, temperature warning if the car becomes too hot/cold, if child has been seated to long or if the child is unintentionally left behind, notifying emergency contacts if needed in case of an accident.

• Linear Side Impact Protection (LSP): Built-in LSP system reduces side impact crash forces on the child

• GreenGuard Gold Certification: Ensures low chemical emissions for healthier indoor air, tested for over 10,000 chemicals

• FR-Free Materials: Naturally flame-resistant materials with no added chemicals for safer use.

• Anti-Rebound Base & SecureFix360 Tether: Minimizes movement in crashes for stability in both rear- and forward-facing positions

• All Around Air Ventilation: Perforated shell and mesh fabrics keep the seat cool and comfortable in all seasons

• Integrated Removable Cup Holders: Dishwasher-safe cup holders keep drinks within reach

• Rear Facing: 4-40 lbs. and 17-43.3 in

• Forward Facing: 26.5-65 lbs. and 33.5-49.2 in

• Booster: 40-120 lbs. and 43.3-57 in. Use from birth to approx. 10 years

• Product Dimensions: 21.7 L x 18.7 W x 35 H

• Weight of Car seat:  35 lbs

    Care Instructions:

    • Machine wash fabric covers separately in cold water, delicate cycle. Do Not Bleach. Drip Dry.
    • Two Removable Cupholders: Dishwasher Safe
    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: 72330404921

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    Hashi Hanta
    Grantham, US
    ★★★★★ 5
    Excelllent book
    Format: Hardcover
    As one of the group of Native Americans who landed on Alcatraz with Richard Oakes, I enjoyed this book. Richard was a fantastic man. A good man.
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    Reviewed in the United States on February 14, 2019
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    Carol
    Bozeman, US
    ★★★★★ 5
    Need to read book
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    The truth about the Native people. THANK YOU Kent for writing this book. We purchased about 12 total.
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    Reviewed in the United States on November 24, 2019
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    Walter Echo-Hawk, author of THE SEA OF GRASS.
    Lowell, 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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    Par
    Draper, 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
    Charlottesville, 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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