Abstract
Data analytics consists of various techniques that need to be used for arriving at the final results. The amount of data coming from various sources is increasing and efficient machine learning methods have to be used for analysis purposes. Machine learning is one of the computing fields that have emerged over the years in various applications like text analytics, speech recognition, fraud detection in financial transactions, retail applications. It forms as the basic step for analytics. The different types of machine learning techniques are regression, classification, clustering, and others. In this chapter, the basics of machine learning are introduced with its key terminologies and its tasks. The different types of tasks that are involved in machine learning are data acquisition, data cleaning, data modeling, and data visualization. These tasks are discussed in this chapter with steps on getting started with machine learning.
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Srinivasa, K.G., G. M., S., H., S. (2018). Basics of Machine Learning. In: Network Data Analytics. Computer Communications and Networks. Springer, Cham. https://doi.org/10.1007/978-3-319-77800-6_8
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DOI: https://doi.org/10.1007/978-3-319-77800-6_8
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