Phillips Collection-PH61030

Marsoni

M251S

$584.50

Get it in 3 business days with 1 day shipping. Friday, May 29

Phillips Collection-PH61030This cast wall art was carefully chosen from a real wood root so we could replicate it in a variety of finishes. We loved the thin branches and how this particular root had a good amount of negative space, so as to not overbear a wall. Can be hung both vertically and horizontally.

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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

New York, 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

Dallas, 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

Grantham, 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

Lake Worth, 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