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Overivew and Tutorial
Jim O’ Donoghue
Deep Learning Meetup @Intercom, Stephens Green
7th April 2016
my background machine learning function elements
hypothesis functions (NN architectures)objective functions
optimisation
my background machine learning function elements
hypothesis functions (NN architectures)objective functions
optimisation
linear regressionmulti-layer perceptron
my background machine learning function elements
input types hypothesis functions (NN architectures)
objective functions + optimisationoutput types
regressionmulti-layer Perceptron
𝜃 = {Weights, bias}
calculate outputs via
interim functionsLinearTanhCoshLogistic SigmoidRecitified Linear
{non linear
Learning deep architectures for AI
https://deeplearning.net
https://github.com/jimod/deeplearning-meetup-dublin
http://colah.github.io/
https://www.coursera.org/learn/machine-learning
https://www.coursera.org/course/neuralnets