what is information theory in data science
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Information theory studies the quantification, storage, and communication of information. It was originally proposed by Claude Shannon in 1948 to find fundamental limits on signal processing and communication operations such as data compression, in a landmark paper titled "A Mathematical Theory of Communication".
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Information theory is an important field that has made significant contribution to deep learning and AI, and yet is unknown to many. Information theory can be seen as a sophisticated amalgamation of basic building blocks of deep learning: calculus, probability and statistics.
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