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Fundamentals of Deep Learning: Designing Next-Generation Machine Intelligence Algorithms
Published 9 hours ago
Description
A technical guide authored by Nikhil Buduma and Nicholas Locascio for designing machine intelligence algorithms. It establishes the field by contrasting traditional computer programming, which relies on rigid instructions, with machine learning, which utilizes models that improve through data-driven examples. The authors explain the biological inspiration behind these systems, describing how artificial neurons and neural networks emulate the human brain's structure to process complex, high-dimensional information. Key technical concepts covered include linear perceptrons, feed-forward networks, and the mathematical implementation of neurons using vector manipulations. Furthermore, the text outlines practical applications and tools, specifically highlighting the use of the TensorFlow library for building and training advanced models. Ultimately, the source serves as a roadmap for understanding hidden layers, optimization techniques, and the architectural "art" of creating next-generation artificial intelligence.
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You can listen and download our episodes for free on more than 10 different platforms:
https://linktr.ee/cyber_security_summary
Get the Book now from Amazon:
https://www.amazon.com/dp/1491925612?lv=shuf&channelId=500&plpRedirect=mhFallback&linkCode=ll2&tag=cvthunderx-20&linkId=f656b5a9c1b46064e53047e09c974312&language=en_US&gaOptInStatus=true&ref_=as_li_ss_tl
Discover our free courses in tech and cybersecurity, Start learning today:
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