SKU: 97915426284

Nintendo Switch Sports Game

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Description

Nintendo Switch Sports GameModel: HACRAS8SA Swing, kick, spike, and bowl your way to victory in a sports collection that will get the whole family movingGet moving with Soccer, Volleyball, Bowling, Tennis, Badminton, and Chambara (Swordplay) using Joy Con controllers! Controls are intuitive, so you can hit the court (or lanes, or field, or arena) and get started. With controlled motions you can curve your bowling ball, add spin to a tennis shot, or even use a Joy Con with the

Model: HACRAS8SA

Swing, kick, spike, and bowl your way to victory in a sports collection that will get the whole family movingGet moving with Soccer, Volleyball, Bowling, Tennis, Badminton, and Chambara (Swordplay) using Joy-Con controllers! Controls are intuitive, so you can hit the court (or lanes, or field, or arena) and get started. With controlled motions you can curve your bowling ball, add spin to a tennis shot, or even use a Joy-Con with the included Leg Strap accessory to kick the ball in a Soccer Shootout. Family and friends can join in on the fun on the same system or online. Plus a seventh sport is planned to be added via a free update this fall; get ready to Golf!Play online and face opponents near and far to earn in-game rewards or aim for the Pro LeagueFace off against opponents worldwide and strive to reach the Pro League in every sport. As you play online in random matchmaking, redeem points you earn for in-game rewards like outfits, sports accessories, gear, and much more for your avatar. The selection of items will rotate each week, so check back and see what’s in stock!Play with friends and family in the same room or across the worldBowl, spike, and duel with friends in all 6 sports! Pass a Joy-Con controller to a friend for some 1v1, 2v2, or a free-for-all that will get everyone moving. In Bowling, all players can bowl simultaneously—no waiting for your turn. Play each game online, or team up with a friend on the same system to take on opponents near and far in team sports like Volleyball and Tennis.The physical version of the Nintendo Switch Sports game includes the Leg Strap accessory to use in Soccer. Or purchase the digital version at a lower price and buy the Leg Strap accessory separately. Additional accessories may be required for multiplayer mode. Sold separately. Any Nintendo Switch Online membership (sold separately) and Nintendo Account required for online features. Not available in all countries. Internet access required for online features. Terms apply. Nintendo Switch Online. Opens in a new window.nintendo.com/switch-online. Be aware of your surroundings. Wear wrist straps and allow adequate room around you during game play.

Product Features:
Swing, kick, spike, and bowl your way to victory in 6 sports
Play Soccer, Volleyball, Bowling, Tennis, Badminton and Chambara (Swordplay)
Motion controls will get you moving and help turn your real-world actions into in-game movements
Use the Leg Strap accessory to kick the ball in a Soccer Shootout or, after a free update this summer, in Soccer matches as well
Play online and challenge random opponents to earn in-game rewards like clothing, gear and much more or reach the Pro League
Play with friends and family locally or online—in some sports, you and a friend can even team up on the same system to take on other teams online
Golf is planned to be added via a free update this fall

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SKU: 97915426284

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4.8 ★★★★★
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Verified Purchase
Richard Hackathorn
Draper, US
★★★★★ 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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Verified Purchase
Amazon Customer
Draper, US
★★★★★ 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
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Verified Purchase
Kindle Customer
Draper, US
★★★★★ 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
T
Verified Purchase
Tommy Jonsson
Dallas, US
★★★★★ 5
Cover many areas in detail and recommendations for more to read for what's outside
Format: Paperback
Good book!
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 4, 2026
M
Verified Purchase
Moses Kayanda
Boise, US
★★★★★ 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

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