Abstract
We combine the Anaconda distribution with the popular Scikit-Learn library to demonstrate a wide range of supervised machine learning algorithms supplemented with unsupervised learning algorithms where appropriate. With clear examples, all written in Python, we demonstrate how these algorithms work to solve machine learning problems.
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© 2020 David Paper
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Paper, D. (2020). Introduction to Scikit-Learn. In: Hands-on Scikit-Learn for Machine Learning Applications. Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4842-5373-1_1
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DOI: https://doi.org/10.1007/978-1-4842-5373-1_1
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Publisher Name: Apress, Berkeley, CA
Print ISBN: 978-1-4842-5372-4
Online ISBN: 978-1-4842-5373-1
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