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Description
cybex sirona swivel car seat Callisto G360 Convertible Car Seat in Salt Lake City Utah – Babinski's BabyThe Callisto G 360 with SafetyAssure Protection System is the ultimate all in one car seat, designed to prioritize your childs safety and comfort at every turn. Offering peace of mind, its equipped with innovative safety features like SensorSafe Smart Technology, which alerts you to unsafe conditions, and the SafeLock One Time Installation system for a secure, worry free setup. Whether youre bringing home a newborn or driving your big kid to school,
The Callisto G 360 with SafetyAssure Protection System is the ultimate all-in-one car seat, designed to prioritize your child’s safety and comfort at every turn. Offering peace of mind, it’s equipped with innovative safety features like SensorSafe Smart Technology, which alerts you to unsafe conditions, and the SafeLock One-Time Installation system for a secure, worry-free setup. Whether you’re bringing home a newborn or driving your big kid to school, the Callisto G 360 grows with your child—from 4 pounds to 65 pounds in harness mode, and up to 120 pounds as a booster seat. Safety has never been this simple, from day one through grade school!
- SAFELOCK 1-TIME INSTALLATION SYSTEM: Fasten the tether to your vehicle's anchor point for added stability. Route the seatbelt through the belt guide, click it into place, close the SafeLock door, and secure the car seat. Tether, Route, Click & Go!
- 360° ROTATION IN ANY RECLINE POSITION: The Callisto G 360 can be rotated toward the car door in any recline position, making it easy to load your child and ensuring you always have the proper recline setup. With five recline options, whether rear or forward-facing, your child is guaranteed a comfortable ride every time.
- SAFETYASSURE PROTECTION SYSTEM IS 37% SAFER*: A complete safety system designed to enhance the car seat’s performance in every situation. It features an Anti-Rebound Base with SecureFix360 Tether, Linear Side-impact Protection, and SensorSafe Bluetooth-enabled chest clip for added peace of mind. The steel frame construction integrates the seat and base, providing reinforced crash protection for superior safety. *Based on head and chest injury metrics as compared to the same seat without these features
- SAFETY TESTING: meets the latest Federal Motor Vehicle Safety Standards for side impact and frontal impact safety (FMVSS 213a, FMVSS 213b)
- ANTI-REBOUND BASE WITH SECUREFIX360 TETHER: Minimizes movement during a crash and ensures maximum stability.
- LINEAR SIDE IMPACT PROTECTION SYSTEM: Effectively reduces crash forces on the child in the event of a side impact collision.
- SENSORSAFE CHEST CLIP: Bluetooth enabled chest clip sends mobile app alerts if a child unbuckles the chest clip, if the back seat becomes too warm or too cold, and if the driver unintentionally leaves the child behind. It also notifies emergency contacts if no action is taken, sharing your location.
- ALL–IN–ONE SEAT: 3 modes of use from birth through elementary school years: Rear-Facing, Forward-Facing and Belt Positioning Booster.
- FIRE RETARDANT CHEMICAL FREE FABRIC: Naturally flame resistant, passing federal safety standards without harmful fire-retardant chemicals.
- REMOVEABLE SUN CANOPY: Adjustable, oversized UPF50+ canopy protects and provides shade for full sun protection.
- 12- POSITION ADJUSTABLE HEADREST AND REMOVEABLE MULTI-STAGE INFANT INSERT: Ensures proper fit and support for your child.
- ALL-AROUND AIR VENTILATION: Mesh fabric details combined with ventilation holes in the shell keep your child cool and comfortable.
- EASY-IN BUCKLE PAD AND INTEGRATED MAGNETIC BUCKLE HOLDERS: Keep the straps and buckles out of the way for hassle-free loading and unloading, making buckling up your child quick and stress-free.
- INTEGRATED REMOVEABLE CUP HOLDERS: The seat includes two integrated, removable cupholders that are dishwasher-safe for easy cleaning.
- MACHINE WASHABLE FABRICS: Spills and messes happen, the Callisto’s premium seat fabric can be washed for easy cleaning.
Usage
- Complies with new FMVSS 213 side impact and frontal impact safety standards
- 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
What's in the box
- Car Seat
- SensorSafe
- Removeable Sun Canopy
- Multi-Stage Infant Insert
- Cup Holders
Specifications
- Product Dimensions: 21.7"L x 18.7"W x 35"H
- Weight: 35 lbs.
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- Free Standard Shipping on $100+ Orders to the USA.
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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]
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4.6 ★★★★★
Based on 24 reviews
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Product Reviews
★★★★★ 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.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on February 14, 2019
★★★★★ 5
Need to read book
Format: Hardcover
The truth about the Native people.
THANK YOU Kent for writing this book.
We purchased about 12 total.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on November 24, 2019
★★★★★ 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.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on April 1, 2019
★★★★★ 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
★★★★★ 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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