This chapter provides an overview of artificial neural networks, with emphasis on their application to classification and labelling tasks. Section 3.1 reviews multilayer perceptrons and their application to pattern classification. Section 3.2 reviews recurrent neural networks and their application to sequence labelling. It also describes the sequential Jacobian, an analytical tool for studying the use of context information. Section 3.3 discusses various issues, such as generalisation and input data representation, that are essential to effective network training.
KeywordsHide Layer Loss Function Gradient Descent Recurrent Neural Network Network Training
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