![【新品】東方Project B2タペストリー 唖采弦二コレクション[1] / KADOKAWA 発売日:2019年12月頃](https://cdn.shopify.com/s/files/1/0270/2812/7807/products/4942330131138.jpg?v=1666986510)
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Description
【新品】東方Project B2タペストリー 唖采弦二コレクション[1] / KADOKAWA 発売日:2019年12月頃201912 FAQ B2 B272. 8cm51. 5cm (C) Illustration
【発売日】2019年12月予定【発送時期】入荷次第発送
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【商品名】とうほうぷろじぇくと
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「東方香霖堂」の挿絵でお馴染み、唖采弦二先生が執筆のタペストリー。
繊細なタッチで描かれた霊夢と魔理沙がB2サイズで堪能できる一品です。
サイズ：B2（約縦72.8cm×横51.5cm）
(C)上海アリス幻樂団 Illustration 唖采弦二
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4.4 ★★★★★
Based on 20 reviews
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Product Reviews
★★★★★ 5
Before GPT can chat, it has to learn.
Format: Paperback
One of the most comprehensive guides to AI and deep learning available. All concepts covered clearly and concisely with illustrations. Complex concepts are broken down into understandable terms. Even though ML and AI require some complex math, you won’t need it to get idea of what’s going on inside the computer’s “brain”.
I use this as a reference when teaching AI concepts and preparing presentations.
I highly recommend it
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Reviewed in the United States on April 5, 2025
★★★★★ 5
Great examples and practical explanations
Format: Paperback
Excellent book. Highly recommend
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 19, 2025
★★★★★ 5
Great for intuitive understanding
Format: Paperback
Amazing book. Great examples and diagrams. If you're looking to get an intuitive grasp of deep learning, look no further. If you're an engineer looking to apply it, I would recommend pairing this with one of the more technical canonical texts and a programming focused book.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 4, 2024
★★★★★ 5
Taught me backpropagation
Format: Paperback
I'm finding this book a great reference to supplement Syracuse IST 691 Deep Learning in Practice. In particular, its explanation of backpropagation is the clearest I have found yet, and that even includes 3 Blue 1 Brown, which always does excellent explanations.
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Reviewed in the United States on April 13, 2025
★★★★★ 5
An Easy Read
Format: Paperback
A good narrative description of how the various systems work. Good for getting a conceptual understanding. No math to speak of, and if you want it, you can refer to the references cited, or your other favorite machine learning book.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 7, 2024
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