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Machine Learning for Developers

You're reading from   Machine Learning for Developers Uplift your regular applications with the power of statistics, analytics, and machine learning

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Product type Paperback
Published in Oct 2017
Publisher Packt
ISBN-13 9781786469878
Length 270 pages
Edition 1st Edition
Languages
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Authors (2):
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Md Mahmudul Hasan Md Mahmudul Hasan
Author Profile Icon Md Mahmudul Hasan
Md Mahmudul Hasan
Rodolfo Bonnin Rodolfo Bonnin
Author Profile Icon Rodolfo Bonnin
Rodolfo Bonnin
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Toc

Table of Contents (10) Chapters Close

Preface 1. Introduction - Machine Learning and Statistical Science 2. The Learning Process FREE CHAPTER 3. Clustering 4. Linear and Logistic Regression 5. Neural Networks 6. Convolutional Neural Networks 7. Recurrent Neural Networks 8. Recent Models and Developments 9. Software Installation and Configuration

Deep neural networks

Now that we have a rich number of layers, it's time to start a tour of how the neural architectures have evolved over time. Starting in 2012, a rapid succession of new and increasingly powerful combinations of layers began, and it has been unstoppable. This new set of architectures adopted the term deep learning, and we can approximately define them as complex neural architectures that involve at least three layers. They also tend to include more advanced layers than the Single Layer Perceptrons, like convolutional ones.

Deep convolutional network architectures through time

Deep learning architectures date from 20 years ago and have evolved, guided for the most part by the challenge of solving the...

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