Abstract
In Chapter 3, we explored a DL use case for regression. We explored the entire problem-solving approach with a business-forward strategy. We leveraged all our learning from Chapters 1 and 2 in foundational DL and the Keras framework to develop DNNs for a regression use case. In this chapter, we will take our learning one step further and design a network for a classification use case. The approach overall remains the same, but there are a few nuances we need to keep in mind while solving a classification use case. Moreover, we will take our learning in this chapter one step ahead with extensive DNN architectures. Let’s get started.
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© 2019 Jojo Moolayil
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Moolayil, J. (2019). Deep Neural Networks for Supervised Learning: Classification. In: Learn Keras for Deep Neural Networks. Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4842-4240-7_4
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DOI: https://doi.org/10.1007/978-1-4842-4240-7_4
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Publisher Name: Apress, Berkeley, CA
Print ISBN: 978-1-4842-4239-1
Online ISBN: 978-1-4842-4240-7
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