Learning Using neural Networks – I | Artificial Intelligence | Video lecture

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Learning Using neural Networks – I

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TOPICS:

Instructional Objectives2:19
Neural Network
History
Why Neural Networks?
Features of the brain
Brain and Machine
Perceptron
Perceptron Learning Rule
Learning algorithm
Gradient Descent
Gradient Ascent
Gradient Descent
Gradient-Descent(training examples 1)
Gradient-Descent(rraining exampIes 1)
Incremental Stochastic Gradient Descent
Linear Separability
Decision Surface of a Perceptron
Decision Surface of a Pe ceptron
Decision Surface of a Perceptron
Linear Neurons
Perceptron limitation
Multi-layer Feed-forward Network
Supervised Learning Backprop
Sigmoidal Neurons
Sigmoid Squashing Function
The Sigmoid Function
Sigmoidal Neurons
Sigmoid Unit
Questions (Lecture 35)

 

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