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Description
maxi cosi car seats Maxi-Cosi Pebble 360 Pro² Car Seat & Base Bundle – Mamas & Papas UKMaxi Cosi Pebble 360 Pro Car Seat Twillic Black Maxi Cosi Pebble 360 Pro Car Seat Twillic Black From the very first day, the Maxi Cosi Pebble 360 Pro prioritises your babys safety and comfort with its full lie flat position, providing maximum sleep comfort. Compatible with the FamilyFix 360 Pro, it combines SlideTech and 360 rotation for easy installation. Uncompromising safety, unmatched comfort, Pebble 360 Pro is there from the start. Product
Maxi-Cosi Pebble 360 Pro² Car Seat - Twillic Black
Maxi-Cosi Pebble 360 Pro² Car Seat - Twillic Black
From the very first day, the Maxi-Cosi Pebble 360 Pro² prioritises your baby’s safety and comfort with its full lie-flat position, providing maximum sleep comfort. Compatible with the FamilyFix 360 Pro, it combines SlideTech® and 360° rotation for easy installation. Uncompromising safety, unmatched comfort, Pebble 360 Pro² is there from the start.
Product Features:
- Pebble 360 ProPro² features an easy-in harness that stays open and out of the way, so you can effortlessly get your child in and out of the car.
- G-CELL Side Impact Protection provides your child with unrivalled safety, spreading the impact and reducing injuries in the event of a collision.
- Meets the highest and latest i-Size safety standards, offering maximum safety for your child.
- Pebble 360 Pro² features an easy-in harness that stays open and out of the way, so you can effortlessly get your child in and out of the car.
- Lifting your baby in and out of the car has never been this comfortable thanks to SlideTech® technology.
- The ergonomic handle lets you carry your baby to and from your car with ease.
- Does your car seat cover need a bit of freshening up? Wipe it down with a damp cloth, or put it in the washing machine up to 30°C.
- Designed with ventilation panels, breathable foam, and comfortable mesh fabrics for enhanced air circulation, ensuring your child stays cosy.
- The extra-large sun canopy with UPF 50+ can be adjusted easily and keeps your baby cool even in the blazing sun.
- Our newborn inlay keeps your little one comfortable while providing a proper fit and room to grow.
- Designed to grow with your baby, offering lasting functionality from birth (40 cm), with the integrated newborn inlay, up to 18 months (87cm).
- As part of the 360 Pro Family, the Pebble 360 Pro² can be used from birth up to 18 months. It’s compatible with the FamilyFix 360 Pro base .
Maxi-Cosi FamilyFix 360 Pro ISOFIX Base – Black
Revolutionary slide-out base makes every day easier
FamilyFix 360 Pro is the only car seat base that rotates and slides toward you using Maxi-Cosi’s patented SlideTech™ technology. The revolutionary sliding car seat technology makes getting your child in and out of the car easier than ever before. No backache, head bangs, or struggles; simply lock, slide, spin, and go!
Product Features
Maxi-Cosi Pebble 360 Pro² Car Seat - Twillic Black
Age Suitability: From birth to approx. 18 months
Health & Safety: ECE R129-03 i-Size
Safety Warning: Please refer to user manual
Composition: PP (Polypropylene), PA (Polyamide), PAGF, POM, Polyester fabrics, PU foam, Polyester wadding, PP plates, Polyester Back-foaming
Care & Maintenance: Fully assembled
Self-Assembly Required?: Please refer to user manual
Maxi-Cosi FamilyFix 360 Pro ISOFIX Base – Black
Age Suitability: From birth to approx. 4 years or 17kg
Health & Safety: ECE R129-03 i-Size
Safety Warning: See instruction manual
Composition: Fabric - Polyester
Care & Maintenance: Please refer to user manual
Self-Assembly Required?Fully Assembled
Maxi-Cosi Pebble 360 Pro² Car Seat - Twillic Black
Dimensions: 75cm x 44cm x 58cm
Weight: 4.7kg
Maxi-Cosi FamilyFix 360 Pro ISOFIX Base – Black
Dimensions:65.4 x 38.8 x 63.2cm
Weight:8.6kg
- The revolutionary sliding car seat technology combined with one-hand 360° rotation to make every day easier for parents. Simply slide, spin and go!
- Pebble 360 Pro² reclines into a full lie-flat position in all modes for maximum sleep comfort – in the car or attached to a pushchair.
- Designed with ventilation panels, breathable foam, and comfortable mesh fabrics for enhanced air circulation, ensuring your child stays cosy.
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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.
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4.6 ★★★★★
Based on 10 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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