Data Science Methods and Machine Learning Algorithm Implementations for Customized Pratical Usage

Due to the unprecedented rise of data content over the last decade, an opportunity for databased personalization and analysis has become a norm in the modern world. By implementing Machine Learning algorithms and Data Science methods no industry remained unchanged. This paper applied these methods a...

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Bibliographic Details
Main Authors: Erol Mrzic, Tarik Zaimovic
Format: Article
Language:English
Published: UIKTEN 2020-08-01
Series:TEM Journal
Subjects:
Online Access:http://www.temjournal.com/content/93/TEMJournalAugust_1179_1185.pdf
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spelling doaj-9b88f1ab1bef487ea9170bd6856bbfac2020-11-25T03:11:35ZengUIKTENTEM Journal2217-83092217-83332020-08-01931179118510.18421/TEM93-44Data Science Methods and Machine Learning Algorithm Implementations for Customized Pratical UsageErol MrzicTarik ZaimovicDue to the unprecedented rise of data content over the last decade, an opportunity for databased personalization and analysis has become a norm in the modern world. By implementing Machine Learning algorithms and Data Science methods no industry remained unchanged. This paper applied these methods and algorithms in personal, practical examples in order to see their benefits in our day-today lives. For the purpose of this case study, we analyzed three cases: a personal movie recommender, messages analysis and real estate trends and predictions on the local market. For this research we used global and personal data, and applied a suitable machine learning model. The purpose of this paper is to establish how one individual, and in what measure, with the use of these new technological tools, can ease his decision making process and manage a more tailored lifestyle.http://www.temjournal.com/content/93/TEMJournalAugust_1179_1185.pdfdata sciencemachine learningpersonal usemessage analysismovie recommenderprice prediction
collection DOAJ
language English
format Article
sources DOAJ
author Erol Mrzic
Tarik Zaimovic
spellingShingle Erol Mrzic
Tarik Zaimovic
Data Science Methods and Machine Learning Algorithm Implementations for Customized Pratical Usage
TEM Journal
data science
machine learning
personal use
message analysis
movie recommender
price prediction
author_facet Erol Mrzic
Tarik Zaimovic
author_sort Erol Mrzic
title Data Science Methods and Machine Learning Algorithm Implementations for Customized Pratical Usage
title_short Data Science Methods and Machine Learning Algorithm Implementations for Customized Pratical Usage
title_full Data Science Methods and Machine Learning Algorithm Implementations for Customized Pratical Usage
title_fullStr Data Science Methods and Machine Learning Algorithm Implementations for Customized Pratical Usage
title_full_unstemmed Data Science Methods and Machine Learning Algorithm Implementations for Customized Pratical Usage
title_sort data science methods and machine learning algorithm implementations for customized pratical usage
publisher UIKTEN
series TEM Journal
issn 2217-8309
2217-8333
publishDate 2020-08-01
description Due to the unprecedented rise of data content over the last decade, an opportunity for databased personalization and analysis has become a norm in the modern world. By implementing Machine Learning algorithms and Data Science methods no industry remained unchanged. This paper applied these methods and algorithms in personal, practical examples in order to see their benefits in our day-today lives. For the purpose of this case study, we analyzed three cases: a personal movie recommender, messages analysis and real estate trends and predictions on the local market. For this research we used global and personal data, and applied a suitable machine learning model. The purpose of this paper is to establish how one individual, and in what measure, with the use of these new technological tools, can ease his decision making process and manage a more tailored lifestyle.
topic data science
machine learning
personal use
message analysis
movie recommender
price prediction
url http://www.temjournal.com/content/93/TEMJournalAugust_1179_1185.pdf
work_keys_str_mv AT erolmrzic datasciencemethodsandmachinelearningalgorithmimplementationsforcustomizedpraticalusage
AT tarikzaimovic datasciencemethodsandmachinelearningalgorithmimplementationsforcustomizedpraticalusage
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