Classification Methods- Episode 7: Artificial Neural Networks

Classification Methods- Episode 7: Artificial Neural Networks

  • 13/10/2021
    1:00 pm - 2:30 pm

Course details

data science seminar | level: intermediate | register now
for questions related to this event, contact ugent@flames-statistics.com
affiliation: Ghent University


Abstract

Neural Networks are a machine learning framework that attempts to simulate the way in which the human brain processes information. A Neural Network is formed from hundreds of single units, artificial neurons or processing elements connected with coefficients (weights), which constitute the neural structure and are organized in layers. The power of neural computations comes from connecting neurons in a network. The power of neural computations comes from connecting neurons in a network. Each processing element has weighted inputs, transfer function and one output. The behavior of a neural network is determined by the transfer functions of its neurons, by the learning rule, and by the architecture itself. The weighted sum of the inputs constitutes the activation of the neuron. The activation signal is passed through a transfer function to produce a single output of the neuron. Using the neuralnet package in R and the Bank loan data set, this seminar explores the basic notions of Neural Networks and demonstrates their usefulness in model predictions.


Prerequisites


Background readings


Fee

Free


Venue

Online


Instructor

Dr Emmanuel Abatih


Free