Genetic Algorithm

Genetic algorithm implementation in neural network

Genetic algorithms (GAs) are a heuristic search and optimisation technique inspired by natural evolution. They have been successfully applied to a wide range of real-world problems of significant complexity.

It is an algorithm that was inspired by the theory of evolution by Charles Darwin. It simulates the process of natural selection where the fittest individuals have higher probabilities to transfer their genes to the next generation. It is usually divided into 5 parts:

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Neural Network Tutorial

C++ Neural Network Backpropagation tutorial from scratch.

In this playlist, I teach the neural network architecture and the learning processes to make the ANN able to learn from a dataset.

The Tutorials are divided in each part of the neural network and we start coding it in C++ in Visual Studio 2017. Once you have completed the tutorial you will be able to design your own neural network and optimize it.

  1. Introduction
  2. Neuron & Layer
  3. Input & Output Layer
  4. Hidden Layer
  5. Neural network
  6. Training
  7. FeedForward & Backpropagation

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