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Description
peg perego compatible car seats Peg Perego Primo Viaggio Convertible Kinetic Car SeatThe Primo Viaggio Convertible is made with the highest quality of materials, providing complete safety and peace of mind to parents of little ones. It offers added safety features like adjustable Side Impact Protection (SIP), Expanded Poly Styrene (EPS) and Expanded Polypropylene (EPP) energy absorbing foam, Anti rebound bar, and Kinetic Pods. Style and Comfort The Primo Viaggio Convertible Kinetic was designed to provide the utmost in safety and
The Primo Viaggio Convertible is made with the highest quality of materials, providing complete safety and peace of mind to parents of little ones. It offers added safety features like adjustable Side Impact Protection (SIP), Expanded Poly Styrene (EPS) and Expanded Polypropylene (EPP) energy-absorbing foam, Anti-rebound bar, and Kinetic Pods.
Style and Comfort
The Primo Viaggio Convertible Kinetic was designed to provide the utmost in safety and fashion. Parents will find the innovative Fresco Jersey performance fabric to comfortably suit their little ones, as well as present a chic and stylish look that would be a welcome addition to any vehicle.
Keep Child Rear Facing Longer
The American Academy of Pediatrics now recommends parents keep their children rear facing until they reach their second birthday, or they reach the maximum height or weight for their seat. The Convertible allows a child to sit rear facing up to 45 lbs., as long as the child's head is at least 1" below the headrest edge. (Please note: Only the lower seven positions can be used in rear-facing mode.)
- Reversible: Can be used rear facing for children 5 to 45 lbs. and forward facing for children 22 to 65 lbs.
- SIP: Side Impact Protection protects child's head, neck, and spine. Easily adjusted to 10 different height positions, even with child in seat. (Please note: Only the lower seven positions can be used in rear-facing mode.)
- Kinetic Pods: Kinetic pods help move forces away from your baby in case of side collision
- EPP + EPS: Energy-absorbing foam, Expanded Polystyrene, in shell. Expanded Polypropylene in the head protects child's body from impact forces.
- ARB: The Anti-rebound bar protects baby by minimizing forces and reducing rotation in case of front or rear collision. The ARB is integrated and stowable.
- ARB Spacer: The Anti-rebound bar spacer allows for extended rear-facing use by increasing your child's leg room by 2 inches / 5cm.
- Energy Management System: Absorbs crash energy with parts designed to bend during a collision, deflecting energy from the child's body. A contoured steel back plate minimizes flexing and reduces forward movement upon impact.
- Quick-Release, 5 point (non-rethread) harness: Made with a "cobblestone" webbing of extra-strong polyester thread; equipped with shoulder pads and chest clip.
- Top Tether Hook: Increases stability in forward facing mode and limits forward movement.
- Easy Tight Latch: Easy tight latch system offers ease of use and installation.
- Tri-Stage Cushion: System is included for comfort and support of a newborn's neck and bottom. As you child grows, cushions can be sequentially removed to keep baby always properly positioned.
- FAA Approved: Certified for use in aircraft
- NHTSA Certified: Certified for use in automobile
- Made in Italy: All PEG baby products are Made in Italy. From concept, to creation, every step in the process is performed by PEG and no one else.
Specifications:
- Seat Dimensions: 26 1/4" x 18 3/4" x 25 3/4"
- Seat Weight: 24.4 lbs.
- Rear-facing child weight: 5 to 45 lbs
- Forward-facing child weight: 26.5 to 65 lbs
- Includes cup holder
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4.2 ★★★★★
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Product Reviews
★★★★★ 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
★★★★★ 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
★★★★★ 5
Cover many areas in detail and recommendations for more to read for what's outside
Format: Paperback
Good book!
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Reviewed in the United States on May 4, 2026
★★★★★ 5
One of the best machine learning books...
Format: Paperback, Format: Paperback
Machine Learning can often be intimidating whether you are starting out or already a practitioner. It is easy to get stuck on one concept, walk away frustrated, or just copy that code you find on StackOverflow without really understanding what it does. What the authors of this book, Machine Learning with PyTorch and Scikit-Learn, have managed to do is to keep the reader engaged giving a deeper illustration as to how the concepts work. In this book, you get practical code examples, a detailed explanation of how the various library tools work, and exposure to the mathematical concepts behind machine learning algorithms. In addition, what I like about the book unlike many machine learning books is that the authors have managed to intuitively explain how each algorithm works, how to use them, and the mistake you need to avoid.
I have not read a Machine Learning book that better explains Transformers as this one does. The authors have managed to give a detailed dive into this model architecture through well-explained codes and illustrations. As a reader, you walk away having intuitively grasped the concepts of attention and self-attention in ways that will make this crucial NLP architecture clear. You get exposed to pre-trained models from HuggingFace library which really helps to have that hands-on experience working with large datasets.
As they have done throughout the book, the authors have broken down those complex mathematical operations into simple explanations that are easy to follow. What I generally like about the book is how it seamlessly connects all the chapters, not throwing off the reader. There are numerous external resources quoted throughout the book. This helps spark that curiosity to dig deeper. In addition, you get introduced to PyTorch, getting exposed to all those sophisticated libraries that help the reader learn how to maximize their compute power. I would say it is not intimidating at all even if you have not used PyTorch before.
I would recommend this book to anybody seeking a textbook that is both easy to read and modern in its content. If were to rate the book I will give it a 10/10 as it really applies to both beginners and experienced practitioners, covers all the concepts one needs to apply in their operations, and acts as a quick reference.
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Reviewed in the United States on March 1, 2022
★★★★★ 5
Thorough Primer for Machine Learning and PyTorch
Format: Paperback
BLUF: A thorough primer for machine learning enthusiasts with plenty of theory to underscore its many practical examples. A definite must-have for anyone looking to add PyTorch to their machine learning tool belt.
PROS:
- Extremely thorough (if not comprehensive). I really appreciate that this book doesn't just thrust one into building models with PyTorch. It starts at the "beginning" and provides examples, theory, additional resources, and citations along the way.
- Theory. Those whose calculus and linear algebra courses ended many years ago will appreciate (if not remember exactly) the mathematical theory and notation that accompanies almost every paragraph. This book gives one the opportunity to "dig deeper" or stay in the shallows until the notation stops.
- Python. Rather than simply utilizing Scikit-Learn to illustrate concepts and introduce models, this book contains many sections where models (such as a Perceptron) are coded from the ground up so the reader can fully understand the underlying mechanics. Python enthusiasts will nerd out. Parents of small children might want to skip a few pages.
- Graphs, charts, and graphics. There are plenty of places where a drier text might have foregone the use of graphs. This text does not. It does however refrain from overusing them.
- PyTorch. This should be obvious from the title, but this text prioritizes PyTorch instead of TensorFlow. This is especially helpful for those looking for an alternative to Keras and TensorFlow as the PyTorch API is very user-friendly.
CONS:
- Almost too much code. This isn't a true "con" but anyone wanting to emulate or follow along with the examples would do well to get the digital edition so they can copy and paste.
- Length and complexity. Anyone hoping for a "quick read" or a "quick start guide" will be disappointed. This book hovers somewhere between an undergraduate primer and a graduate-level text for length and readability. This is not to say that it's difficult to read, merely that there are other "quick start" / "practical" texts out there that cater more to a lay audience.
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Reviewed in the United States on February 26, 2022