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Arbiter - Hyperparameter Optimization

Arbiter is a library for hyperparameter optimization of neural networks. Hyperparameter optimization refers to the process of automating the selection of network hyperparameters (learning rate, number of layers, etc) in order to obtain good performance. It is part of the Deeplearning4j suite of software.

Automated hyperparameter search is necessary when the optimization search is too large for a human to manually tune. Arbiter helps by doing this through multiple methods, including random search, grid search, and Bayesian methods.

Chris Nicholson

Chris Nicholson is the CEO of Skymind and co-creator of Deeplearning4j. In a prior life, Chris spent a decade reporting on tech and finance for The New York Times, Businessweek and Bloomberg, among others.

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