Presentation titled "A Brief Review of Hyperparameter Optimization Methods for Machine Learning" for Research Methods in Computer Science course at Ryerson University
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Updated
Dec 2, 2017 - HTML
Presentation titled "A Brief Review of Hyperparameter Optimization Methods for Machine Learning" for Research Methods in Computer Science course at Ryerson University
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Hypergeometric distribution mode.
Returns a normalized node package representation by either specifying an object or a file path.
The Catla Project
This project is divided in a two parts. In first study, Lame parameters are identified using tanh activation function. After that, six activation functions are analysed on the basis of minimum loss, training time and convergence order for different error norms.
Geometric distribution median.
Bernoulli distribution entropy.
Command-line Arguments Parser with JSX support
An egg plugin for validating parameters
Degenerate distribution expected value.
Parameter validation module for Python methods
Self adapting differential evolution algorithm for system identification
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