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Description
baby stroller sets Black/Gold Premium 3-in-1 Baby Stroller (Car Seat & Base Included)The Premium 3 in 1 Baby Stroller includes the car seat and ISOFIX car seat base. It is the ultimate companion for any parent on the go. This stroller is designed with both style and functionality in mind, featuring a sleek and modern design, premium materials, and a range of convenient features that make your life as a parent easier. This stroller features smooth rolling wheels that make it easy to navigate, even on uneven surfaces. The front wheels
- The Premium 3-in-1 Baby Stroller includes the car seat and ISOFIX car seat base. It is the ultimate companion for any parent on the go. This stroller is designed with both style and functionality in mind, featuring a sleek and modern design, premium materials, and a range of convenient features that make your life as a parent easier.
- This stroller features smooth-rolling wheels that make it easy to navigate, even on uneven surfaces. The front wheels are equipped with our smooth 360° swivel feature, allowing for effortless maneuverability, making it easy to steer through tight spaces such as busy streets or crowded malls. The rear wheel is also large and sturdy, providing stability and support for your little one.
- The lightweight design and easy-fold feature make this stroller incredibly portable and easy to take on the go. Whether you're running errands around town, traveling, or just taking a leisurely stroll in the park, our Premium 3-in-1 Baby Stroller with car seat & base is the perfect choice for any parent.
- PACKAGE CONTAINS – 3-in-1 stroller frame, bassinet, car seat, ISOFIX base.
- 6 FREE GIFTS – Included with the package are 6 free gifts! You will receive a big mami diaper bag, seat mattress, mosquito net, summer mattress, rain cover, foot cover.
- 3-IN-1 VERSATILITY – Effortlessly transition the bassinet into a pushchair in just three simple moves, catering to your baby's need to sit, sleep, or be carried.
- EASILY PUT TOGETHER – Our premium quality baby stroller is easily put together in a matter of minutes and comes in a wide assortment of colors.
- ANTI-SHOCK WHEELS – Anti-shock durable rubber wheels have 360° swiveling, which gives this baby stroller a refined and smooth ride with superb maneuverability.
- EASILY FOLDABLE – This baby stroller can be folded with just one hand – with or without the seat attached and it automatically locks and stands upright when folded.
- SUPER SUSPENSION – The dual frame and seat suspension work together for smoother strolling and a more stable ride.
- BUILT TO LAST – Sturdy, durable and anti-rust aluminum alloy frame holds a child up to 55 lbs, for years of comfortable strolling and making it ultra-convenient for moms on-the-go; Suitable age: 0-36 months
- HASSEL FREE CLEANING – Say goodbye to stubborn stains! Our stroller's materials are designed to resist spills. In the event of a mess, simply wipe down with a damp cloth and mild detergent.
- NON-TOXIC MATERIALS – All of the components are made of non-toxic high-quality materials that will never break on you. The quality of this item is exactly what you would imagine for the price. Simply the best you can get!
- TAKE WITH YOU ANYWHERE – Our baby stroller is designed with travel in mind. Its compact fold ensures it fits effortlessly into car trunks, overhead compartments in planes, and tight storage spaces.
Specifications:
- Material: Premium PU Leather & Linen Cloth, Lightweight Aluminum Alloy Frame, High Resistance Rubber Wheels
- Product Weight: Entire Set 35 LBS / Stroller 23 LBS
- Weight Capacity: Up to 50 LBS
- Recommended Age for Bassinet: Up to 48 months
- Recommended Age for Car Seat: Up to 15 months
Safety & Convenience Features:
- 32.3 Inches Sitting Height
- 14.2 Inches Inside Bassinet Width
- 47 Inches Handlebar Height
- Ergonomic Bassinet & Car Seat Padding for Spine Support
- One Foot Stop Operation Smooth & Efficient Braking
- Easy Dual-Button Sitting & Lying Mode Adjustment
- 30 Days Day Satisfaction Guarantee
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4.4 ★★★★★
Based on 15 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