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automl package fits from simple regression to highly customizable deep neural networks either with gradient descent or metaheuristic, using automatic hyper parameters tuning and custom cost function. A mix inspired by the common tricks on Deep Learning and Particle Swarm Optimization.

(Key words: autoML, Deep Learning, Particle Swarm Optimization, learning rate, minibatch, batch normalization, lambda, RMSprop, momentum, adam optimization, learning rate decay, inverted dropout, particles number, kappa, regression, logistic regression)

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.