The popularity of data has exponentially grown in the last decade, to such a level that it has been defined "the world’s most valuable resource" (The Economist, May 16th 2017). This led many universities and researchers to divert their focus into what is called now data science, where machine learning algorithms are exploited to study data in order to make predictions or classifications. While the concept of neural networks may be considered widely spread, i.e. making predictions and learning from input datasets using fictitious structures that emulate the human brain, there are other approaches that are taken towards exploiting machine learning techniques in a faster, more power-efficient way.