z-logo
open-access-imgOpen Access
The Difference of Machine Learning and Deep Learning Algorithms
Author(s) -
Yew Kee Wong
Publication year - 2021
Language(s) - English
Resource type - Conference proceedings
DOI - 10.5121/csit.2021.111519
Subject(s) - big data , computer science , machine learning , artificial intelligence , analytics , data analysis , data science , variety (cybernetics) , predictive analytics , software analytics , business intelligence , data mining , software , software development , software construction , programming language
In the information era, enormous amounts of data have become available on hand to decision makers. Big data refers to datasets that are not only big, but also high in variety and velocity, which makes them difficult to handle using traditional tools and techniques. Due to the rapid growth of such data, solutions need to be studiedand provided in order to handle and extract value and knowledge from these datasets. Machine learning is a method of data analysis that automates analytical model building. It is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention. Such minimal human intervention can be provided using big data analytics, which is the application of advanced analytics techniques on big data. This paper aims to analyse some of the different machine learning algorithms and methods which can be applied to big data analysis, as well as the opportunities provided by the application of big data analytics in various decision making domains.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here