Introduction

Various paradigms of earning problems
Issues in deep learning framework

Perspectives
review of fundamental learning techniques

Feed forward neural network

Artificial Neural Network
multi-layer neural network
operations

activation function
cardinality
properties of fuzzy relations

Training Neural Network

Risk minimization
backpropagation
model selection

loss function
regularization
optimization

Conditional Random Fields

Linear chain
Markov network
Training CRFs
Entropy

partition function
Belief propagation
Hidden Markov Model

Deep Learning

Deep Feed Forward network
training deep models
Convolutional Neural Network
Deep Belief Network

regularizations
dropouts
Recurrent Neural Network

Deep Learning research

Object recognition
computer vision

sparse coding
natural language

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