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
  7 Hours
 

Number of participants


Starts

Ends


Dates are subject to availability and take place between 09:30 and 16:30.
Open Training Courses require 5+ participants.

Testimonials (3)

Related Courses

Related Categories