Machine learning is not all about autonomous vehicles and terminator robots. Techniques such as principle component analysis (PCA) can be combined with other data exploration techniques to help us gain a deeper understanding of the world around us. Many machine learning (ML) techniques aspire to reduce the complexity of data to simplify comparison and classification. Computational techniques for analysing characteristics of ‘things’ can help to identify patterns and attributes which can be used to identify thing such as which species of plant a cell belongs to, what are the key drivers for business profitability, and what traits are common in certain diseases.
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