Deep Learning: Fundamentals and Applications

One Billion Knowledgeable · Kulandiswa nge-AI ngu-Mason (kusukela ku-Google)
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Izilinganiso nezibuyekezo aziqinisekisiwe  Funda Kabanzi
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What Is Deep Learning


Deep learning belongs to a larger family of machine learning approaches that are founded on artificial neural networks and representation learning. This family of methods is known as deep learning. There are three different ways to learn: supervised, semi-supervised, and unsupervised.


How You Will Benefit


(I) Insights, and validations about the following topics:


Chapter 1: Deep learning


Chapter 2: Machine learning


Chapter 3: Neural coding


Chapter 4: Scale space


Chapter 5: Compressed sensing


Chapter 6: Reservoir computing


Chapter 7: Echo state network


Chapter 8: Stochastic parrot


Chapter 9: Differentiable programming


Chapter 10: Liquid state machine


(II) Answering the public top questions about deep learning.


(III) Real world examples for the usage of deep learning in many fields.


(IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of deep learning' technologies.


Who This Book Is For


Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of deep learning.

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