Overview
The training is aimed at people who want to learn the basics of neural networks and their applications.
Course Outline
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