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abt neural network & it's application for seminar

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Neural Network Guided by Chapala Maharana Submitted By- Nilmani Singh Branch-CSE Regd. No.-0601289251
Contents .Introduction to Neural Network .Neurons .Activation Function .Types of Neural Network .Learning In Neural Networks .Application of Neural Network .Advantages of Neural Network .Disadvantages Of Neural Network
Neural Networks ,[object Object]
A powerful technique to solve many real world problems.
The ability to learn from experience in order to improve their performance.
Ability to deal with incomplete information,[object Object]
Developed in 1943
Comprised of one or more layers of neurons
Several types, we’ll focus on feed-forward and feedback networks,[object Object]
Neural Network Neurons Receives n-inputs Multiplies each input by its weight Applies activation function to the sum of results Outputs result
Activation Functions Controls when unit is “active” or “inactive” Threshold function outputs 1 when input is positive and 0 otherwise Sigmoid function = 1 / (1 + e-x)
Types of Neural Networks Neural Network types can be classified based on following attributes: ,[object Object], - Static (feedforward) - Dynamic (feedback) ,[object Object], - Single layer - Multilayer - Recurrent ,[object Object], - Supervised - Unsupervised - Reinforcement
Classification Based On Connection Types ,[object Object]
Dynamic(Feedback)Classification Based On Topology ,[object Object]
Single layer
Multilayer(unit delay operator z-1implies dynamic system)
Classification Based On Learning Method Supervised Unsupervised Reinforcement Supervised learning ,[object Object]
At each presentation: adapt weights
After many epochs convergence to a local minimum,[object Object]

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neural network