This is a laboratory module with some hints at theoretical basis. First, an introduction to the development environment chosen, i.e. the Anaconda package. Second, some basic concepts about object-orientation. Afterwards, some considerations about the design of a neural network as a class and the main blocks of the code. A glance follows at the datasets and how they have been scaled in order to improve performance. Then a hint about possible future developments of the code in sight of deep networks and, finally, some indications about running the sample code.

Deep Learning 03 - Laboratory - Mafalda Neural Network code

Cristina De Castro
2018

Abstract

This is a laboratory module with some hints at theoretical basis. First, an introduction to the development environment chosen, i.e. the Anaconda package. Second, some basic concepts about object-orientation. Afterwards, some considerations about the design of a neural network as a class and the main blocks of the code. A glance follows at the datasets and how they have been scaled in order to improve performance. Then a hint about possible future developments of the code in sight of deep networks and, finally, some indications about running the sample code.
2018
Istituto di Elettronica e di Ingegneria dell'Informazione e delle Telecomunicazioni - IEIIT
object-orientation
Anaconda
neural networks
python
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/376639
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