Jarwan; Ayman Sabbah; Mohamed Ibnkahla
In usual ways of programming, a program is built by building instructions in order to reach desired outputs from inputs. However, in machine learning (ML), that process is flipped. The inputs and desired set of outputs are given, and the program should learn what instructions or policy should be followed. ML is concerned with algorithms that observe data, learn from it, grow up, and make more intelligent decisions. Based on the way that machines accumulate knowledge and become able to function as needed, ML can be classified into supervised, semi-supervised, unsupervised, and reinforcement learning.
A. Jarwan, A. Sabbah, and M. Ibnkahla, “Machine Learning in Wireless Sensor Networks for the Internet of Things,” in Encyclopedia of Wireless Networks, X. (Sherman) Shen, X. Lin, and K. Zhang, Eds. Cham: Springer International Publishing, 2018, pp. 1–7. doi: 10.1007/978-3-319-32903-1_274-1.
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