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Description
yugioh battles of legend armageddon booster box Yu-Gi-Oh CCG: Battles of Legend - Chapter OneBattles of Legend: Chapter 1 brings you an encore performance for many of the most popular cards from Battles of Legend: Lights Revenge, Battles of Legend: Relentless Revenge, Battles of Legend: Heros Revenge, and Battles of Legend: Armageddon, plus related cards from other past releases! Highlights of this massive set include: The return of long awaited monsters like Number 90: Galaxy Eyes Photon Lord and Chaos Emperor, the Dragon of Armageddon.
Battles of Legend: Chapter 1 brings you an encore performance for many of the most popular cards from Battles of Legend: Light’s Revenge, Battles of Legend: Relentless Revenge, Battles of Legend: Hero’s Revenge, and Battles of Legend: Armageddon, plus related cards from other past releases!Highlights of this massive set include:
★ The return of long-awaited monsters like Number 90: Galaxy-Eyes Photon Lord and Chaos Emperor, the Dragon of Armageddon.
★ Another crack at the unearthly, Astral-language version of Number 39: Utopia, originally released in Battles of Legend: Armageddon!
★ Six new collectible dice, each sporting a popular monster design including Cyber Dragon, Judgment Dragon, or Elemental HERO Stratos.
Each Battles of Legend: Chapter 1 box contains a grand total of:
• 1 Secret Rare
• 6 Ultra Rares (in different name colors)
• 30 Commons
• 1 of 6 collectible dice
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4.3 ★★★★★
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Product Reviews
★★★★★ 5
An enjoyable, and seriously excellent, path to understanding Deep Learning...
Format: Paperback
Deep Learning is changing our world. If you want to understand more, this is a great place to start. Andrew Glassner is a talented explainer - I took his short course on Deep Learning and learned so much, but also came away impressed at how well he can make complex material so clear and engaging. And this book is jammed packed with insights, visuals, and clear explanations. The author has a playful, sometimes quirky style that shines through, which gives this tour a lot of personality as well as information. Very enjoyable reading - I felt like he captured all that was good about his course (and then some) and bottled it up in this book. There is a lot more material here than in that course, and it is well laid-out and organized so that it is easy to roam around and come back to review the pieces that matter to you.
Even if you plan to go to on to be a world-class Deep Learning engineer or mathematician, you have to start by understanding the concepts. And this book does a great job of presenting all the core ideas in a way that makes them clear and memorable.
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Reviewed in the United States on August 5, 2021
★★★★★ 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
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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.
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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