Ignition Coil - 1 Ohm - (17-6806)

Marsoni

M251S

$20.00

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

Ignition Coil - 1 Ohm - (17-6806)Ignition Coil 55mm center to center with 7mm mount holes. 1. 0 OHM Primary Fits: Contact point magnetos or CDI ignitions. OEM Ref # 5G4 82310 40 00 355 82310 40 00 24X 82310 10 367 82310 30 1M2 92310 10 336 82310 10 43G 92310 10 5X6 82310 10 Part Number: 17 6806

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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

West Palm Beach, 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

San Leandro, 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

Carnegie, 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

Waukegan, 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