CFP last date
16 December 2024
Reseach Article

A Practical Guide of Machine Learning Algorithms and Applications

by Hassan Kassim Albahadily, Malik Qasim Mohammed, Ali Kassim Mohammed
International Journal of Applied Information Systems
Foundation of Computer Science (FCS), NY, USA
Volume 12 - Number 40
Year of Publication: 2023
Authors: Hassan Kassim Albahadily, Malik Qasim Mohammed, Ali Kassim Mohammed
10.5120/ijais2023451938

Hassan Kassim Albahadily, Malik Qasim Mohammed, Ali Kassim Mohammed . A Practical Guide of Machine Learning Algorithms and Applications. International Journal of Applied Information Systems. 12, 40 ( April 2023), 8-13. DOI=10.5120/ijais2023451938

@article{ 10.5120/ijais2023451938,
author = { Hassan Kassim Albahadily, Malik Qasim Mohammed, Ali Kassim Mohammed },
title = { A Practical Guide of Machine Learning Algorithms and Applications },
journal = { International Journal of Applied Information Systems },
issue_date = { April 2023 },
volume = { 12 },
number = { 40 },
month = { April },
year = { 2023 },
issn = { 2249-0868 },
pages = { 8-13 },
numpages = {9},
url = { https://www.ijais.org/archives/volume12/number40/1133-2023451938/ },
doi = { 10.5120/ijais2023451938 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2023-07-05T19:11:36.844394+05:30
%A Hassan Kassim Albahadily
%A Malik Qasim Mohammed
%A Ali Kassim Mohammed
%T A Practical Guide of Machine Learning Algorithms and Applications
%J International Journal of Applied Information Systems
%@ 2249-0868
%V 12
%N 40
%P 8-13
%D 2023
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This article examines the primary subcategories of machine learning: supervised learning, unsupervised learning, and reinforcement learning. Along with decision trees, random forests, artificial neural networks, SVMs, boosting and bagging algorithms, and BP algorithms, it also examines other well-known machine learning techniques. Through the development of theoretical systems, furthering the development of autonomous learning capacities, integrating multiple digital technologies, and promoting customized, bespoke services, the objective is to increase public awareness of machine learning and hasten its rate of adoption.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Artificial Intelligence Machine Learning Algorithms Machine Learning Applications