SKU: 13577460081
maxi-cosi 360 pebble

maxi-cosi 360 pebble Maxi-Cosi Pebble 360 Pro2 autostoel – Tiny Library

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Description

maxi-cosi 360 pebble Maxi-Cosi Pebble 360 Pro2 autostoel – Tiny LibraryThe Maxi Cosi Pebble 360 Pro 2 in Twillic Green offers maximum safety and exceptional comfort from the very first ride. This i Size car seat is suitable from birth to approximately 15 months (4087 cm) and grows smoothly with your baby. 360 rotatable in combination with the FamilyFix 360 Pro base G CELL side impact protection for optimal protection 3 reclining positions , including a completely flat position ClimaFlow & mesh upholstery for perfect

The Maxi-Cosi Pebble 360 Pro 2 in Twillic Green offers maximum safety and exceptional comfort from the very first ride. This i-Size car seat is suitable from birth to approximately 15 months (40–87 cm) and grows smoothly with your baby.

✓ 360° rotatable in combination with the FamilyFix 360 Pro base
✓ G-CELL side impact protection for optimal protection
✓ 3 reclining positions , including a completely flat position
✓ ClimaFlow & mesh upholstery for perfect temperature regulation

The Pebble 360 Pro 2 car seat meets the stringent i-Size standard and is designed to optimally protect your child, even in a side impact. The easy-in harness stays open, so you can quickly and easily place your baby in the seat. Combined with the separately available FamilyFix 360 Pro base, you can easily rotate and slide the seat towards you—ideal for your back and for everyday use.

Comfort has also been considered: the three recline positions, including a completely flat position suitable for both car and stroller use, ensure a natural sleeping position. The adjustable headrest grows with your child, and the breathable ClimaFlow fabric with mesh panels maintains a comfortable temperature at all times. The included infant insert provides extra support for newborns, ensuring your child is safe and snug from day one.

In the box:
The product consists of the Pebble 360 Pro2 car seat including Baby Hugg seat reducer and sun canopy

Product specifications:

  • Suitable for children from 40 - 87 cm
  • Designed to grow with your baby, providing continued functionality from birth (40cm), with the integrated newborn inlay, up to 18 months (87cm).
  • Protected on the road: in the car, on the stroller and on the plane
  • G-CELL Side-impact technology
  • ISOFIX connections
  • Can be combined with Maxi-Cosi Familyfix 360 Pro
  • Compatible with the Maxi-Cosi Leona2, Soho buggy and Maxi-Cosi Fame stroller.
  • When used with the base Maxi-Cosi Familyfix 360 Pro: SlideTech™ and 360° one-handed rotation
  • Easy-in harness: a harness that stays open and out of the way, making it easy to get your child in and out of the car.
  • Certified as back-friendly by AGR
  • Ergonomic carrying handle
  • Equipped with ClimaFlow temperature regulating fabric
  • Sustainable Eco Care materials: Made from soft, 100% recycled fabric.
  • Complies with the strict i-Size safety standard
  • TÜV approved for aircraft use
  • Machine washable: Wipe with a damp cloth or machine wash up to 30°C.
  • Extra large sun canopy
  • Dimensions: 58 x 66 x 44 cm
  • Car seat weight: 4.7 kg

 

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Exchange/Return Notes
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SKU: 13577460081

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Walter Echo-Hawk, author of THE SEA OF GRASS.
Lexington, 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.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on April 1, 2019
P
Verified Purchase
Par
Lexington, 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.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on December 20, 2024
R
Verified Purchase
Richard Hackathorn
Port Orchard, 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
Omaha, 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
Omaha, 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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