Using AI / machine learning to solve real world problems

The field of Artificial Intelligence and Machine learning has made great advancements over the past few decades and has become more intertwined into the daily lives of people. With the development of technology, it is common to see machine learning methods used and adopted to help solve real-worl...

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Main Author: Lok, Ignatius Zhengrong
Other Authors: Ng Wee Keong
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2021
Subjects:
Online Access:https://hdl.handle.net/10356/148035
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1480352021-04-22T06:10:47Z Using AI / machine learning to solve real world problems Lok, Ignatius Zhengrong Ng Wee Keong School of Computer Science and Engineering AWKNG@ntu.edu.sg Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence The field of Artificial Intelligence and Machine learning has made great advancements over the past few decades and has become more intertwined into the daily lives of people. With the development of technology, it is common to see machine learning methods used and adopted to help solve real-world problems of both individuals and well as large corporations. This project studies how different machine learning algorithms can be used to aid companies make better business decisions and to optimize their investments. In this particular project, we look to help TFI decide on new restaurant investments and potential locations. This is done by predicting the expected annual revenues of Turkish Restaurant based on the data given. The data provided is very imbalanced with a significantly larger test data compared to the training data. Additionally, the data provided contained obfuscated variables which encoded different categorical data types including Demographic, Real Estate and Commercial Data. We look to address the obfuscated data and the small training set during the preprocessing and feature engineering stage. Different supervised machine learning models including Random Forests, Support Vector Machines, XGBoost, LGBM and Ensemble learning methods are then applied to predict the restaurant revenue, allowing a better decision to be made when opening new restaurants and to increase the effectiveness of investments in new restaurant sites. Bachelor of Engineering (Computer Science) 2021-04-22T06:10:47Z 2021-04-22T06:10:47Z 2021 Final Year Project (FYP) Lok, I. Z. (2021). Using AI / machine learning to solve real world problems. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/148035 https://hdl.handle.net/10356/148035 en SCSE20-0095 application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
spellingShingle Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
Lok, Ignatius Zhengrong
Using AI / machine learning to solve real world problems
description The field of Artificial Intelligence and Machine learning has made great advancements over the past few decades and has become more intertwined into the daily lives of people. With the development of technology, it is common to see machine learning methods used and adopted to help solve real-world problems of both individuals and well as large corporations. This project studies how different machine learning algorithms can be used to aid companies make better business decisions and to optimize their investments. In this particular project, we look to help TFI decide on new restaurant investments and potential locations. This is done by predicting the expected annual revenues of Turkish Restaurant based on the data given. The data provided is very imbalanced with a significantly larger test data compared to the training data. Additionally, the data provided contained obfuscated variables which encoded different categorical data types including Demographic, Real Estate and Commercial Data. We look to address the obfuscated data and the small training set during the preprocessing and feature engineering stage. Different supervised machine learning models including Random Forests, Support Vector Machines, XGBoost, LGBM and Ensemble learning methods are then applied to predict the restaurant revenue, allowing a better decision to be made when opening new restaurants and to increase the effectiveness of investments in new restaurant sites.
author2 Ng Wee Keong
author_facet Ng Wee Keong
Lok, Ignatius Zhengrong
format Final Year Project
author Lok, Ignatius Zhengrong
author_sort Lok, Ignatius Zhengrong
title Using AI / machine learning to solve real world problems
title_short Using AI / machine learning to solve real world problems
title_full Using AI / machine learning to solve real world problems
title_fullStr Using AI / machine learning to solve real world problems
title_full_unstemmed Using AI / machine learning to solve real world problems
title_sort using ai / machine learning to solve real world problems
publisher Nanyang Technological University
publishDate 2021
url https://hdl.handle.net/10356/148035
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