Abstract
The primary task of this tutorial is to introduce interested students into the principles of Machine Learning. Since a generally accepted theoretical frame is missing and the results achieved so far are scattered across hundreds of algorithms developed for diverse applications, the paper is conceived rather pragmatically. Its objective is to expose the most typical and illustrative approaches. After studying them, the reader should be able to write simple machine-learning algorithms and should have an idea how to deepen his or her knowledge about some specific area of interest. The introductory parts present a unifying view of the most common notions.
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© 1992 Springer-Verlag Berlin Heidelberg
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Kubat, M. (1992). Introduction to machine learning. In: MÅ™rÃk, V., Å tÄ›pánková, O., Trappl, R. (eds) Advanced Topics in Artificial Intelligence. Lecture Notes in Computer Science, vol 617. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-55681-8_33
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DOI: https://doi.org/10.1007/3-540-55681-8_33
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