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.
Parameter validation module for Python methods
Self adapting differential evolution algorithm for system identification
Design of PageRank algorithm for link analysis in JavaScript.
Different ways of passing parameters to a .NET C# method.
Geometric distribution standard deviation.
Negative binomial distribution mode.
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