Autoencoder

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    Categories: Data Science

    A neural network whereby the unsupervised learning algorithm is trained to set the output target values equal to the inputs. The autoencoder’s goals are to reduce the number of random variables under consideration, such that the input is represented in fewer dimensions (see Dimension Reduction).

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    Justin Chan
    Dr Chan founded DataDrivenInvestor.com (DDI) and is the CEO for JCube Capital Partners. Specialized in strategy development, alternative data analytics and behavioral finance, Dr Chan also has extensive experience in investment management and financial services industries. Prior to forming JCube and DDI, Dr Chan served in the capacity of strategy development in multiple hedge funds, fintech companies, and also served as a senior quantitative strategist at GMO. A published author at professional journals in finance, Dr. Chan holds a Ph.D. degree in finance from UCLA.