Abstract
The focus of machine learning is to develop algorithms that can learn from data [1]. The traditional approach to solving a data-driven problem is to build an algorithm that describes a systematic procedure of calculations specifically for the problem [2]. However, data from experiments or observations is often noisy and building such an algorithm for high-dimensional data is not feasible in most scenarios. Machine learning offers a solution to this problem. Instead of looking at the observations by hand and manually finding patterns in the data, machine learning “gives the computers the ability to learn without being explicitly programmed” [3].
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© 2016 Springer Fachmedien Wiesbaden
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Kroiss, M. (2016). Introduction. In: Predicting the Lineage Choice of Hematopoietic Stem Cells. BestMasters. Springer Spektrum, Wiesbaden. https://doi.org/10.1007/978-3-658-12879-1_1
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DOI: https://doi.org/10.1007/978-3-658-12879-1_1
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Publisher Name: Springer Spektrum, Wiesbaden
Print ISBN: 978-3-658-12878-4
Online ISBN: 978-3-658-12879-1
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