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 Mcclouh & Pits (1943)
 Hebb‘s (1949)
 Widrow & Hoff (1959)
 Hopfield Network(1962)
 Kohnen & Andresen(1972)
Artificial intelligence.
Artificial neural network is a non-linear computational system.
“NEURAL NETWORK”.
Better solving complex problems.
Input layer, hidden layers and output layer.
A NEURAL NETWORK
A BIOLOGICAL NEURON
Fundamental block is Neuron.
 A simple neural network consists of :
• three layers,
• activation function,
• learning technique,
• weights.
All these layers consist of neurons which are
interconnected to form a network.
• Feed Forward Network
• Feedback Network
• One direction
• No loops
• No feedback
 Natural Language Processing problems that can be
solved using neural networks. As we showed,
neural networks have many applications such as
 Pattern Classification
 Prediction And Financial Analysis
 Control and Optimization
 Face recognition
 In many cases, neural networks methods
outperform other methods.
 Artificial neural networks have application in
many areas as medical, business, agriculture, for
prediction purpose, classification purpose and
many others areas.
 By using artificial neural networks is that the
results are MORE ACCURATE, MEASURABLE
AND ERRORLES.
 Artificial Neural Networks can use cure and
prevent from lung cancer disease and also useful
in other industrial area. Performance of ANN can
be improved by using suitable optimization
technique as Ant colony Optimization.
PRESENTED BY :
PRIYA JOT

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Basic Introduction to Neural Networks

  • 1.
  • 2.  Mcclouh & Pits (1943)  Hebb‘s (1949)  Widrow & Hoff (1959)  Hopfield Network(1962)  Kohnen & Andresen(1972)
  • 3. Artificial intelligence. Artificial neural network is a non-linear computational system. “NEURAL NETWORK”. Better solving complex problems. Input layer, hidden layers and output layer.
  • 6. Fundamental block is Neuron.  A simple neural network consists of : • three layers, • activation function, • learning technique, • weights. All these layers consist of neurons which are interconnected to form a network.
  • 7.
  • 8.
  • 9. • Feed Forward Network • Feedback Network
  • 10. • One direction • No loops • No feedback
  • 11.
  • 12.  Natural Language Processing problems that can be solved using neural networks. As we showed, neural networks have many applications such as  Pattern Classification  Prediction And Financial Analysis  Control and Optimization  Face recognition  In many cases, neural networks methods outperform other methods.
  • 13.  Artificial neural networks have application in many areas as medical, business, agriculture, for prediction purpose, classification purpose and many others areas.  By using artificial neural networks is that the results are MORE ACCURATE, MEASURABLE AND ERRORLES.  Artificial Neural Networks can use cure and prevent from lung cancer disease and also useful in other industrial area. Performance of ANN can be improved by using suitable optimization technique as Ant colony Optimization.