NDLI: AI vs. Machine Learning vs. Deep Learning

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AI vs. Machine Learning vs. Deep Learning

Content Provider	Scilit
Author	Lalitha, R.
Copyright Year	2021
Description	Artificial intelligence (AI), machine learning (ML), and deep learning (DL) are subsets of one another, and they are interrelated to each other. But each can be applied and used in many different ways to get the desired solution for a problem. Hence, understanding the differences and similarities among them is essential to use them in the right way. Therefore, this chapter provides an overview of the meaning of AI, ML, and DL with a broad comparison based on their features, merits, demerits, and implementation process. The implementation process and the common programming languages used for implementing AI, ML, and DL algorithms are discussed in brief. The main objective of this chapter is to understand when to use AI, ML, and DL? Where to apply AI, ML, and DL? Why to use AI, ML, and DL? How to use AI, ML, and DL. They are explained with real-time examples to provide a clear understanding in these areas. The outcome of this chapter makes the reader realize and appreciate the basic concept which says that deep learning is the subset of machine learning and machine learning is the subset of artificial intelligence. The examples given to understand the applications of artificial intelligence, machine learning, and deep learning will help the readers to know how and where the algorithms are applied. Book Name: Artificial Intelligence (AI)
Related Links	https://api.taylorfrancis.com/content/chapters/edit/download?identifierName=doi&identifierValue=10.1201/9781003005629-3&type=chapterpdf
Ending Page	82
Page Count	10
Starting Page	73
DOI	10.1201/9781003005629-3
Language	English
Publisher	Informa UK Limited
Publisher Date	2021-04-25
Access Restriction	Open
Subject Keyword	Book Name: Artificial Intelligence (ai) Cybernetical Science Machine Learning Deep Learning Artificial Intelligence Implementation
Content Type	Text
Resource Type	Chapter

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