Introduction
  • Introduction
Artificial Intelligence Basics
  • Why to learn artificial intelligence and machine learning?
  • Types of artificial intelligence learning methods
Hopfield Neural Network Theory
  • Hopfield neural network introduction
  • Hopfield network - weights
  • Hopfield neural network - Hebbian learning
  • Hopfield neural network - energy
  • Measuring the energy of the network
  • Hopfield neural network example
  • Hopfield networks quiz
Hopfield Neural Network Implementation
  • Hopfield network implementation - utils
  • Hopfield network implementation - matrix operations
  • Hopfield network implementation - network
  • Hopfield network implementation - running the algorithm
Neural Networks With Backpropagation Theory
  • Artificial neural networks - inspiration
  • Artificial neural networks - layers
  • Artificial neural networks - the model
  • Why to use activation functions?
  • Neural networks - the big picture
  • Using bias nodes in the neural network
  • How to measure the error of the network?
  • Optimization with gradient descent
  • Gradient descent with backpropagation
  • Backpropagation explained
  • Applications of neural networks I - character recognition
  • Applications of neural networks II - stock market forecast
  • Deep learning
  • Types of neural networks
  • Neural networks quiz
Single Perceptron Model
  • Perceptron model training
  • Perceptron model implementation I
  • Perceptron model implementation II
  • Perceptron model implementation III
  • Trying to solve XOR problem
  • Conclusion: linearity and hidden layers
Backpropagation Implementation
  • Structure of the feedforward network
  • Backpropagation implementation I - activation function
  • Backpropagation implementation II - NeuralNetwork
  • Backpropagation implementation III - Layer
  • Backpropagation implementation IV - run
  • Backpropagation implementation V - train
Logical Operators
  • Logical operators introduction
  • Running the neural network: AND
  • Running the neural network: OR
  • Running the neural network: XOR
Clustering
  • Clustering with neural networks I
  • Clustering with neural networks II
Classification - Iris Dataset
  • About the Iris dataset
  • Constructing the neural network
  • Testing the neural network
  • Calculating the accuracy of the model
Optical Character Recognition (OCR)
  • Optical character recognition theory
  • Installing paint.net
  • Transform an image into numerical data
  • Creating the datasets
  • OCR with neural network
Course Materials (DOWNLOADS)
  • Course materials