Autonomous learning machine for big online data analytics
Deep learning became very popular recently, as it is capable of tackling problems that humans are unable to solve through traditional programming. In this paper, we will go over the implementation of a deep learning model known as Autonomous Deep Learning(ADL), which is capable of being fully fle...
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2021
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sg-ntu-dr.10356-1486562021-05-14T08:21:56Z Autonomous learning machine for big online data analytics Yeap, Bryan Kian Hon Mahardhika Pratama School of Computer Science and Engineering mpratama@ntu.edu.sg Engineering::Computer science and engineering Deep learning became very popular recently, as it is capable of tackling problems that humans are unable to solve through traditional programming. In this paper, we will go over the implementation of a deep learning model known as Autonomous Deep Learning(ADL), which is capable of being fully flexible and has a self-growing network that adapts to the demand of its dataset by growing its hidden layers and nodes. This is especially important in a non-stationary dataset where data sources can come from different origins.Next, we convert ADL to fit in the context of regression, which is called Autonomous Learning Machine (ALM). Afterwards, we will use it to analyze real-world data of the remaining useful life of aircraft gas turbine engines. Lastly, the experimental results will be summarised and compared with results from other machine learning models. Bachelor of Engineering (Computer Science) 2021-05-14T08:21:56Z 2021-05-14T08:21:56Z 2021 Final Year Project (FYP) Yeap, B. K. H. (2021). Autonomous learning machine for big online data analytics. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/148656 https://hdl.handle.net/10356/148656 en application/pdf Nanyang Technological University |
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Engineering::Computer science and engineering Yeap, Bryan Kian Hon Autonomous learning machine for big online data analytics |
description |
Deep learning became very popular recently, as it is capable of tackling problems that
humans are unable to solve through traditional programming. In this paper, we will go
over the implementation of a deep learning model known as Autonomous Deep
Learning(ADL), which is capable of being fully flexible and has a self-growing network
that adapts to the demand of its dataset by growing its hidden layers and nodes. This
is especially important in a non-stationary dataset where data sources can come from
different origins.Next, we convert ADL to fit in the context of regression, which is
called Autonomous Learning Machine (ALM). Afterwards, we will use it to analyze
real-world data of the remaining useful life of aircraft gas turbine engines. Lastly, the
experimental results will be summarised and compared with results from other
machine learning models. |
author2 |
Mahardhika Pratama |
author_facet |
Mahardhika Pratama Yeap, Bryan Kian Hon |
format |
Final Year Project |
author |
Yeap, Bryan Kian Hon |
author_sort |
Yeap, Bryan Kian Hon |
title |
Autonomous learning machine for big online data analytics |
title_short |
Autonomous learning machine for big online data analytics |
title_full |
Autonomous learning machine for big online data analytics |
title_fullStr |
Autonomous learning machine for big online data analytics |
title_full_unstemmed |
Autonomous learning machine for big online data analytics |
title_sort |
autonomous learning machine for big online data analytics |
publisher |
Nanyang Technological University |
publishDate |
2021 |
url |
https://hdl.handle.net/10356/148656 |
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1701270525150494720 |