Real-time scalable parallel data stream classification
The main objective of this final master project is to create a real-time prototype that is capable of classifying real-time data using several deep learning algorithms. Classifying means to give "valuable" information ¿ that maybe can be unknown - to the different incoming data. Note also...
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| Formato: | tesis de maestría |
| Fecha de publicación: | 2018 |
| País: | España |
| Recursos: | Universitat Oberta de Catalunya (UOC) |
| Repositorio: | O2, repositorio institucional de la UOC |
| OAI Identifier: | oai:openaccess.uoc.edu:10609/83465 |
| Acesso em linha: | http://hdl.handle.net/10609/83465 |
| Access Level: | acceso abierto |
| Palavra-chave: | big data High Performance Computing artificial intelligence Apache Kafka deep learning aprenentatge profund intel·ligència artificial computació d'alt rendiment inteligencia artificial aprendizaje profundo computación de alto rendimiento Big data -- TFM Dades massives -- TFM Datos masivos -- TFM |
| Resumo: | The main objective of this final master project is to create a real-time prototype that is capable of classifying real-time data using several deep learning algorithms. Classifying means to give "valuable" information ¿ that maybe can be unknown - to the different incoming data. Note also that this could be extrapolated to other fields. In addition, some research will be done in the field of deep learning with the aim of giving some guidelines about how big data can be classified in a cluster environment. The idea of developing this prototype is to prove that large amounts of data processing can be tackled within this methodology. Further work can be done following this line with the purpose of creating a real data-time analysis methodology that can be applicable to other fields such us medical studies, economic statistics, mobility solutions and many others. As in all research studies, iterative processing must be done in order to enhance and/or update the deep algorithms that will be presented during this final master project. |
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