Machine Learning:A Review

Isonkobong Christopher Udousoro (Department of Information Technology, School of Computing and Information Technology, Federal University of Technology, Owerri.)

Abstract


Due to the complexity of data, interpretation of pattern or extraction of information becomes difficult; therefore application of machine learning is used to teach machines how to handle data more efficiently. With the increase of datasets, various organizations now apply machine learning applications and algorithms. Many industries apply machine learning to extract relevant information for analysis purposes. Many scholars, mathematicians and programmers have carried out research and applied several machine learning approaches in order to find solution to problems. In this paper, we focus on general review of machine learning including various machine learning techniques. These techniques can be applied to different fields like image processing, data mining, predictive analysis and so on. The paper aims at reviewing machine learning techniques and algorithms. The research methodology is based on qualitative analysis where various literatures is being reviewed based  on machine learning.


Keywords


Machine learning;Supervised learning;Unsupervised learning;Reinforcement learning;Semi-supervised learning;Multitask learning;Ensemble Learning;Neural Network;Instance-Based

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References


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DOI: https://doi.org/10.30564/ssid.v2i2.1931

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