SKU: 7127324118

The Phoenix Unchained: Book One of the Enduring Flame

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Description

The Phoenix Unchained: Book One of the Enduring FlameNew York Times and USA Today bestselling authors Mercedes Lackey and James Mallory first teamed up to write The Obsidian Trilogy, set in a wondrous world filled with magical beings, competing magic systems, and a titanic struggle between good and evil. That world proved so popular with the creators and readers alike that Lackey and Mallory have returned to it with The Phoenix Unchained, Book One of The Enduring Flame, the opening volume of a new epic

New York Times and USA Today bestselling authors Mercedes Lackey and James Mallory first teamed up to write The Obsidian Trilogy, set in a wondrous world filled with magical beings, competing magic systems, and a titanic struggle between good and evil.
That world proved so popular with the creators and readers alike that Lackey and Mallory have returned to it with The Phoenix Unchained, Book One of The Enduring Flame, the opening volume of a new epic fantasy trilogy.
After a thousand years of peace, much Magick has faded from the world. The Elves live far from humankind. There are no High Mages, and Wild Mages are seen only rarely. Bisochim, a powerful Wild Mage, is determined to reintroduce Darkness to the world, believing that it is out of Balance.

Tiercel, a young Armethalian nobleman, is convinced that High Magic is not just philosophy. He attempts a spell--and draws the unwelcome attention of Bisochim. Tiercel survives Bisochim's attack and begins trying to turn himself into a High Mage.

Next in line to be Harbormaster of Armethalieh, Harrier instead finds himself regularly saving Tyr's life and meeting magickal people and creatures. To Harrier's dismay, it seems that he must become a hero.

In The Phoenix Unchained, Harrier and Tiercel begin a marvelous journey to uncover their destinies. Along the way, they meet a charming female centaur, several snooty Elves, and the most powerful dragon their world has ever known.

Binding Type: Paperback
Publisher: Tor Books
Published: 08/26/2008
ISBN: 9781250163967
Pages: 400
Weight: 0.95lbs
Size: 8.00h x 5.00w x 0.89d
Accelerated Reader Quiz #/Name: 164743 / Phoenix Unchained
Reading Level: 6.5 / Interest Level: Upper Grade / Point Value: 20
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SKU: 7127324118

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R. Cote
West Palm Beach, US
★★★★★ 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
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Rafael Azevedo Souza Costa
Belleville, US
★★★★★ 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
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Thomas
Lexington, US
★★★★★ 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
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La Monte HP Yarroll
Port Orchard, US
★★★★★ 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
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3rd Act
Dallas, US
★★★★★ 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.
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Reviewed in the United States on May 7, 2024

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