SKU: 168020375

玩出無限潛力的0-3歲五感遊戲書：日本最強部落客媽咪設計的50個啟蒙刺激，讓孩子越玩越聰明【首刷限量贈品版】（限量贈品：富樂夢12色六角油畫棒）

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玩出無限潛力的0-3歲五感遊戲書：日本最強部落客媽咪設計的50個啟蒙刺激，讓孩子越玩越聰明【首刷限量贈品版】（限量贈品：富樂夢12色六角油畫棒）: : X Instagram 500 3 [] X [] X [] X [] X [] 12100 0 3 1. 2. 50Instagram 2050 3. 0 30 3 4. 5. 0 3 6. 7. 19761 9 1922 1987

作者: 中山芳一  |  譯者: 陳芷盈

遊戲是沒有目的的教育，聰明，是玩出來的！
日本兒童全方位教育專家 X 超人氣Instagram媽咪部落客
 
嚴選50款0-3歲在家簡單遊戲的方法
 
（（（　五大主題遊戲　）））
玩出　 [表達力]　X　[思考力]　X　[好奇心]　X　[運動能力]　X　[專注力]
最重要的，是讓孩子樂在其中！
 
　　※首刷限量隨書贈：富樂夢12色六角油畫棒（市值：100元）
 
　　0-3歲是孩子的黃金成長期也是學習大爆發時期，與其用「能做到與不能做？」到來評價孩子，不如觀察他們喜歡哪個遊戲或是投入在何種遊戲的視角來守護孩子吧。
 
　　只要父母用心陪伴，透過遊戲就能創造孩子未來的大潛力！
 
本書特色
 
　　1. 不以掌握特定能力為目的來遊戲：雖然書中提供每款遊戲能幫助孩子掌握的能力，但請作為一個大致目標即可。重視孩子對遊戲「好開心！」、「好想玩！」、「還想再玩！」的心情才是最重要的。希望家長能豐富自家的「在家遊戲」時光。
　　
　　2. 嚴選50種啟發遊戲：藉由日本兒童教育專家從Instagram 上20萬款適合兒童發展的遊戲中，收錄50款媽媽們最希望孩子能培養的能力、且在家就可輕鬆實施的遊戲進行分類。
 
　　3. 掌握0-3歲孩子的學習大爆發時期：0-3歲是孩子的黃金成長期，也是蒙特梭利教育「敏感期」最顯著的時期，藉由孩子不斷從環境吸收感官、運動與語言資訊的重要階段，為孩子量身設計最適合的學習活動。
 
　　4. 材料簡單、製作簡易：使用居家隨手可得的材料進行簡易的製作，不需花費大量金錢購買特殊教具，就能激發孩子最棒的天賦。
 
　　5. 標示不同年齡階段適合的遊戲：書中的遊戲方法根據0-3歲孩子的年齡階段進行分類，確保提供適切的學習和發展。
 
　　6. 提供各款遊戲能帶給孩子的發展項目作為參考：不僅提供遊戲方法，也解釋每一種遊戲如何促進孩子的發展領域，諸如專注力、五感、語言、數學到科學、藝術、社交能力。
 
　　7. 不同領域的作者共同設計：本書作者背景包含職能治療師、教保員及玩具設計師，並由日本知名兒童全方位教育副教授共同擬定。作者的多元背景確保內容的綜合性及專業性，讓每款遊戲都有助於孩子全面發展。
 
　　除此，在育兒路上，針對不同年齡層的孩子的教養問題，本書也給予許多客觀建議。


作者

監修者
 
中山 芳一
 
　　岡山大學教育推進機構 准教授
　　專攻教育方法學。1976年1月生，日本岡山縣人。
　　從事大學生職涯諮詢教育外，也致力於提升幼兒乃至中小學、高中生等各年齡層孩子與青少年非認知能力與後設認知能力。
　　此外，也參與許多針對在職人士的回流教育以及全國地各地產、官、學、法人機構的教育計畫設計。
　　基於從事學童保育現場逾9年的實務經驗，他的座右銘為「實踐本位研究」。
 
譯者
 
陳芷盈
 
　　國立政治大學台灣史研究所博士、東京大学大学院 総合文化研究科特別聴講学生。著有博士論文《台灣酒類產銷之研究（1922-1987）》。
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Adam
Carnegie, US
★★★★★ 4
Too Dry.
Format: Hardcover
This was a required textbook for my class in college. I think it was too dry. The book titled Deep Learning: From Curiosity To Mastery is much more approachable.
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Reviewed in the United States on May 22, 2026
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Amazon Customer
Charlottesville, US
★★★★★ 5
Comprehensive! The Bible of Deep Learning!
This book has by far surpassed my expectations! I have purchased many machine learning and deep neural network books in the past, but nothing has ever come close to this book! First of all, it is written by the fathers of Deep Learning, and is therefore an authority. Secondly, the book is broken into three parts: 1. A math overview and refresher. 2. Deep Learning applications and 3. Research in Deep Learning. I can't help but go through this book from front to back. It is a smooth read, and every sentence written is meaningful. These guys know their stuff! And after you read this book, YOU WILL ALSO know your stuff! If you feel daunted by the price, just remember, you get what you pay for! I'd say they could easily charge about $300+ for this book, but they are doing everyone a very kind favor by ONLY charging this reasonable amount. You get A LOT of bang for your buck with this purchase. I hesitated at first about buying this book because of the price, but I am soooooo happy that I did! Worth every penny! Look no further, get this book and start your Deep Learning journey!!
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Reviewed in the United States on July 14, 2017
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mackster
Alexandria, US
★★★★★ 1
A rushed, poorly written guide of how the "experts" can't really explain what Deep Learning is
Format: Hardcover
This book, in every sense of the word, is rushed. I think the authors wanted to establish themselves as leaders of this young-ish field, but does so by sacrificing quality. It also shows that Deep Learning theory has been there for a long time, known by another name called Neural Networks. The interesting algorithms are of MLP, Back Propagation and the classical neural networks. The optimization methods such as Adam are the ones that are new and interesting, and the only ones worthy of in this book. So, essentially, what you get from this book is use A for X, B for Y and C for Z type of dry, un-intuitive, badly written waste of paper. As for the structure of the book, it's like an example of how not to structure a book. It has some linear algebra, probability at the start (not good enough, and confuses more people and wastes paper). Goes on to prove other algorithms such as PCA (yeah, ok!). Then, talks about how this architecture works for this and that architecture. So, yeah, if you really want to try out deep learning, don't buy this book. Set up Tensorflow/pytorch/ other library, run the tutorials, find an architecture for the problem you are interested in and start tweaking that. You will have far more fun and would have saved your money. The praise that this book gets is beyond me. Did Musk even read this book? I doubt it.
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Reviewed in the United States on May 15, 2018
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Stergios Papadimitriou
West Palm Beach, US
★★★★★ 5
The classic textbook on Deep Learning
Format: Hardcover
Deep Learning is the promising direction towards general purpose effective artificial intelligence. There is an explosion of fruitful research in recent years and a lot of applications pursued mainly from technology giants as Google, Amazon, etc. and outstanding research institutions. The book "Deep Learning " by Ian Goodfellow, Yoshua Bengio, Aaron Gourville, is an excellent piece of work. They manage to present rather difficult things in an understandable manner. The theoretical presentation is outstanding typical of "classic" books. Also, the book stays close to the practical applicability of all the methods and discusses applications extensively. There are a lot of other useful books on deep learning that follow a more practical approach by focusing on a particular deep learning software package, but this one book is certainly much more essential since it provides the required theoretical background in order to be able to do serious work on deep learning. I consider the book as "must have" for anyone that works on deep learning either in an academic or in an industrial environment.
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Reviewed in the United States on August 25, 2018
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Sabrina
Lowell, US
★★★★★ 5
100% Recommend
Format: Paperback
Invincible Compendium One completely lived up to the hype. From the very first chapter, I was hooked by the story, the action, and the character development. What starts off feeling like a classic superhero story quickly becomes something much deeper, darker, and way more emotional than expected. The artwork is incredible and the fight scenes are intense without feeling repetitive. Every character feels important and layered, especially Mark and Omni-Man. The pacing is excellent for such a massive collection, and it’s hard to put down once you start reading. If you’re a fan of superhero comics but want something with real stakes, shocking twists, and strong storytelling, this is absolutely worth reading. Easily one of the best graphic novels I’ve picked up in a long time.
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Reviewed in the United States on May 23, 2026

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