Representation

Representation refers to the process of transforming data from one form to another, while preserving its meaning. In data science and artificial intelligence, representation is a crucial step in the modeling process, as it determines how the data will be interpreted and used by the algorithm. The choice of representation can greatly impact the accuracy and efficiency of the model. There are various types of representation, including numerical, symbolic, and graphical. Numerical representation involves transforming data into a set of numbers, while symbolic representation involves using symbols or tokens to represent data. Graphical representation involves visualizing data through graphs or charts. In machine learning, representation learning is a subfield that focuses on automatically learning the most useful representations of data, without the need for manual feature engineering.
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