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Description
britax isofix booster seat Britax UpNGo Click Backless Booster Car Seat with LATCHThe UpNGo Click backless seat booster gives your child the boost they need to move up into the final car seat stage and go anywhere with confidence. Designed for children from 40 120 lbs and 46 63", this booster combines the portability and convenience that parents look for with kid approved comfort and style. The rigid LATCH connectors click in with ease and release in seconds, making it easy to move the seat between vehicles. UpNGo Click is
The UpNGo™ Click backless seat booster gives your child the boost they need to move up into the final car seat stage and go anywhere with confidence. Designed for children from 40-120 lbs and 46”-63", this booster combines the portability and convenience that parents look for with kid-approved comfort and style. The rigid LATCH connectors click in with ease and release in seconds, making it easy to move the seat between vehicles. UpNGo Click is innovatively designed with PosturePlus™ to help encourage proper posture and seat belt positioning. It also includes a shoulder belt guide to help keep the seat belt in the right place. The slim 17.1” SpaceSaver™ design means there’s more room for siblings or carpoolers, and the soft cushioning and large, padded armrests give your child that extra boost of comfort. Whether they're heading out for a shopping trip with grandma or hopping in with a friend on their way to a sleepover, they’ll feel confident navigating big-kid trips with this lightweight and easy-to-carry booster. They can keep their favorite after-school snacks and drinks close at hand in the two cup holders, which are dishwasher-safe for easy cleanup. The booster seat cover is safe to machine wash and dry, and it’s naturally flame-retardant with no added FR chemicals. The color-coded belt guides help kids learn how to buckle up correctly as they make the final car seat transition, setting them up for safety no matter where their journey takes them.
- Boost, Buckle, Go: Belt-positioning booster lifts your child up to use the vehicle seat belt.
- Extended Maximum Capacity: Designed for children from 40-120 lbs and 46”-63".
- Click On, Quick Off: Steel rigid LATCH connectors click in with ease and release in seconds so you can move between cars with no hassle, making this the perfect travel booster. No more twisted or tangled straps – just a simple connection!
- PosturePlus™ Contoured Seat: Helps encourage proper posture and seat belt positioning.
- SpaceSaver™ Design: 17.1” seat leaves plenty of room for siblings & carpoolers! This slim booster seat is designed to fit 3 across in most vehicles without compromising safety or comfort. *Britax cannot guarantee 3-across fitment in all vehicles.
- Lightweight & Portable: Thanks to the built-in carry handle and lightweight design, you can take this booster anywhere. Weighing under 5 lbs, it’s easy for both caregivers and kids to carry.
- Removable SafeWash® Cover: Safe to machine wash and dry.
- Naturally Flame-Retardant Fabrics: No added FR chemicals.
- Designed for Comfort: Kids can enjoy every ride thanks to the contoured seat with breathable foam and soft padding. Plus, the large, padded armrests provide that extra boost of comfort.
- 2 Dishwasher-Safe Cup Holders: Keep drinks and snacks within reach; easy to remove for cleaning between rides.
- Padded Carry Handle Cover: Helps ensure a comfortable grip.
- Color-Coded Belt Guides: Help kids learn how to buckle up safely.
- Shoulder Belt Guide: Helps keep the shoulder belt in the correct position, encouraging proper fitment as your big kid continues to grow.
- Sleek & Stylish: This no-back booster seat features a sleek, tonal look with neutral colors, soft and smooth knit fabric, and textured mélange cushioning.
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4.0 ★★★★★
Based on 6 reviews
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Product Reviews
★★★★★ 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
★★★★★ 4
Just learning it
Format: Paperback
Nice learning book just have to finish it
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Reviewed in the United States on December 10, 2025