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Investigating the Behaviour of Deep Neural Networks for Classification

Phil Kim's 'Deep Learning with Matlab' book in Python

A FEED-FORWARD DEEP NEURAL NETWORK with:
  • Batch Normalization
  • Activation Functions
  • Delta Error Rule
  • Backward Error Propagation
  • Weight Update Optimization Techniques
  • Drop-Outs
Some Results:
Experiment 1:

NoDropOutNoBatchNorm

Experiment 2:

NoDropOutBatchNorm

Experiment 3:

DropOutNoBatchNorm

Experiment 4:

DropOutBatchNorm

Project Hypothesis

DOI

Email: oasomefun@ieee.org
Somefun, O.A.

(c) 2017

About

Investigating the Behaviour of Deep Neural Networks for Classification

www.researchgate.net/project/Investigating-the-Behaviour-of-Deep-Neural-Networks

Topics

deep-neural-networks deep-learning optimization images dropout batch-normalization numbers classification gradient-descent backpropagation-learning-algorithm rmsprop softmax cross-entropy adamax black-and-white relu

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BSD-3-Clause license
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Oct 7, 2018

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