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Machine Learning: A Concise Overview

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Data Science in Practice

Part of the book series: Studies in Big Data ((SBD,volume 46))

Abstract

Machine learning is a sub-field of computer science that aims to make computers learn. It is a simple view of this field, but since the first computer was built, we have wondered whether or not they can learn as we do.

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Notes

  1. 1.

    There are other classes of machine learning algorithms: semi-supervised, reinforcement learning, recommender system. In this chapter, we focus on the two most popular ones. We refer [32] to the readers for classes not covered here.

  2. 2.

    For some representations, zero is not a good initial value. Random values from 0 to 1 work in most of cases.

  3. 3.

    Select a small value to \(\alpha \), say 0.01, plot \(J(\varTheta )\) to identify how the gradient is converging, increase \(\alpha \) (e.g., doubling its value) up to have an expected convergence.

  4. 4.

    Multiplication is \(O(n^2)\), and inverse is \(O(n^3)\).

  5. 5.

    F\(_1\)-score is a specialization of F\(_{\beta }\)-score that is not covered in this chapter.

  6. 6.

    Definition of eigenvectors can be found in traditional books of linear algebra.

  7. 7.

    For the sake of simplicity, we consider an invalid value (e.g., mixed characters and numerical values) for a feature as missing data too.

  8. 8.

    Also known as multivariate or multi-output regression.

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Acknowledgements

Denio Duarte is partially funded by Coordenadoria de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) under process number 88881.119081/2016-01—Brazil during his visit to Skövde Artificial Intelligence Laboratory (SAIL) at University of Skövde (HiS).

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Authors and Affiliations

  1. Universidade Federal da Fronteira Sul, Chapecó, Brazil

    Denio Duarte

  2. University of Skövde, Skövde, Sweden

    Denio Duarte & Niclas Ståhl

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  1. Denio Duarte
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  2. Niclas Ståhl
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Correspondence to Denio Duarte .

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  1. University of Skövde, Skövde, Sweden

    Alan Said

  2. University of Skövde, Skövde, Sweden

    Vicenç Torra

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Duarte, D., Ståhl, N. (2019). Machine Learning: A Concise Overview. In: Said, A., Torra, V. (eds) Data Science in Practice. Studies in Big Data, vol 46. Springer, Cham. https://doi.org/10.1007/978-3-319-97556-6_3

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