Machine Learning con TensorFlow

Bonilla Pardo, Víctor (2018). Machine Learning con TensorFlow. Proyecto Fin de Carrera / Trabajo Fin de Grado, E.T.S. de Ingenieros Informáticos (UPM), Madrid, España.

Description

Title: Machine Learning con TensorFlow
Author/s:
  • Bonilla Pardo, Víctor
Contributor/s:
Item Type: Final Project
Degree: Grado en Ingeniería Informática
Date: January 2018
Subjects:
Faculty: E.T.S. de Ingenieros Informáticos (UPM)
Department: Inteligencia Artificial
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

En la actualidad, vivimos en una sociedad totalmente conectada
a Internet. La cantidad
ingente de datos en bruto
generados hora tras hora
y el aumento progresivo de los
recursos hardware
ha ocasionado el auge del Aprendizaje Automático y las Redes
Neuronales Artificiales.
En este documento se recoge una introducción
a las Redes de Neuronas Artificiales.
Desde un enfoque teórico se presentan los fundamentos de las Redes Neuronales
clásicas y las arquitecturas de las Redes Neuronales
empleadas hoy en día
.
Asimismo, se
muestra
cómo
implementar los diseños descritos por
la
teoría
mediante el
lenguaje de programación Python y la librería TensorFlow para resolver, primero un
problema clásico, y posteriormente para resolver
y experimentar con
un problema de la
plataforma web Kaggle.---ABSTRACT---Currently, humans live in a s
ociety
completely connected to the Internet. The enormous
amount of raw data generated every hour and the progressive rise in the hardware
resources has caused the boom in Machine Learning and Artificial Neural Networks.
This document contains an introduct
ion to Artificial Neural Networks.
From a
theoretical
approach,
the fundaments of classic Neural Networks and the architecture of
the Neural Networks used nowadays.
Also,
it
shows how to implement the designs described
by the theory with the
programming la
nguage Python and the TensorFlow library to solve, firstly a classic
problem, and afterwards to solve and experiment with a problem from the Kaggle web
platform.

More information

Item ID: 49683
DC Identifier: https://oa.upm.es/49683/
OAI Identifier: oai:oa.upm.es:49683
Deposited by: Biblioteca Facultad de Informatica
Deposited on: 12 Mar 2018 08:31
Last Modified: 12 Mar 2018 08:32
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