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peg perego primo viaggio car seat base Peg Perego Primo Viaggio 4/35 Nido K Infant Car Seat with Base – Dear-Born BabyCrafted in Italy, the Primo Viaggio 4 35 Nido K ensures your little one experiences a cocoon of safety from their very first journey. This innovative car seat boasts two key features that deliver distinct layers of protection. The premium base, equipped with a Load Leg and integrated Anti Rebound Bar, collaborates to minimize rotation in the event of a collision by 50%. Additionally, the Kinetic pods enhance side impact protection. The Load Leg offers
Crafted in Italy, the Primo Viaggio 4-35 Nido K ensures your little one experiences a cocoon of safety from their very first journey. This innovative car seat boasts two key features that deliver distinct layers of protection. The premium base, equipped with a Load Leg and integrated Anti-Rebound Bar, collaborates to minimize rotation in the event of a collision by 50%. Additionally, the Kinetic pods enhance side impact protection. The Load Leg offers flexibility with its adjustable positions, capable of folding under the base when not in use. In the event of a crash, the Energy Management Foot at the base of the Load Leg crumples, diverting and absorbing energy away from the baby.
To shield your child from the elements, the car seat features an extendable Pagoda Hood, providing nearly complete coverage. Mesh side netting ensures ventilation for optimal airflow, while the hood's fabric boasts UPF 50+, guarding against harmful ultraviolet rays. The Primo Viaggio 4-35 Nido K comes complete with a Dual Stage Cushion System, designed to adapt to your baby's growth. The first stage supports a newborn's neck and bottom, while the enlarged second stage offers increased protection and comfort. Adjusting the headrest is a breeze, with six different positions available without the need for re-threading, even when your infant is seated.
Features:
- SIP headrest easily adjusts to 6 different positions with no re-threading even with the infant in the seat
- Energy absorbing EPS foam throughout shell and head panel protects the infant's head and torso from impact forces
- New kinetic pods help to move the force away from baby in case of a side collision
- Load Leg can be adjusted 10 different positions and has an Energy Management Foot that absorbs energy by crumpling upon impact
- Built-in anti-rebound bar attached to base provides superior protection in case of collision
- Extendable Pagoda UPF 50+ Hood has an easy to use zipper allows hood to extend forward, completely protecting baby from the elements
- 100% FIRE RETARDANT FREE: Free of harmful chemicals, the breathable Fresco Jersey fabric is naturally Fire Retardant
- Dual Stage Cushions: Stage 1 for infants 4 lbs and up offers extra support on newborn's neck and bottom; Stage 2 correctly supports growing baby. Both help to keep baby's head properly positioned and are made of Fresco Jersey soft and breathable fabric
- A European belt path and innovative handlebar belt path allows for easy installation without the base, also allowing the handle to act as a anti rebound bar
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4.0 ★★★★★
Based on 26 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.
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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.
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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.
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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