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Practical Machine Learning Cookbook by Atul Tripathi

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Chapter 11. Deep Learning

In this chapter, we will cover the following recipe:

Recurrent neural networks - predicting periodic signals

Introduction

Most of the machine learning algorithms work well due to predefined representations and input features. Machine learning algorithms optimize weights to best make a final prediction, while representation learning attempt to automatically learn good features or representations. Deep learning algorithms attempt to learn at multiple levels of representation by increasing complexity. Deep architectures are composed of multiple levels of non-linear operations, such as neural nets with many hidden layers. The main goal of deep learning techniques is to learn feature hierarchies. Deep learning techniques can ...

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