Introduction to the Use of Neural Networks Training Course

The Basics

• Whether computers can think of?
• Imperative and declarative approach to solving problems
• Purpose Bedan on artificial intelligence
• The definition of artificial intelligence. Turing test. Other determinants
• The development of the concept of intelligent systems
• Most important achievements and directions of development

Neural Networks

• The Basics
• Concept of neurons and neural networks
• A simplified model of the brain
• Opportunities neuron
• XOR problem and the nature of the distribution of values
• The polymorphic nature of the sigmoidal
• Other functions activated
• Construction of neural networks
• Concept of neurons connect
• Neural network as nodes
• Building a network
• Neurons
• Layers
• Scales
• Input and output data
• Range 0 to 1
• Normalization
• Learning Neural Networks
• Backward Propagation
• Steps propagation
• Network training algorithms
• range of application
• Estimation
• Problems with the possibility of approximation by
• Examples
• XOR problem
• Lotto?
• Equities
• OCR and image pattern recognition
• Other applications
• Implementing a neural network modeling job predicting stock prices of listed

Problems for today

• Combinatorial explosion and gaming issues
• Turing test again
• Over-confidence in the capabilities of computers