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Computational Intelligence Algorithms

This work contains a collection of computational implementations of classical algorithms in Optimization, Machine Learning, and Linear Algebra. The project is structured as a set of independent modules, each focusing on a specific problem or class of methods.

Introduction

The objective of this work is to explore and implement fundamental algorithms from different domains, emphasizing:

  • Mathematical modeling
  • Algorithmic problem solving
  • From-scratch implementations
  • Visualization of results (when applicable)

Each module is self-contained and demonstrates a specific technique or family of algorithms.

Requirements

See requirements.txt for the project dependencies.

About

Collection of from-scratch implementations of core Computational Intelligence algorithms, including Gaussian Elimination, Genetic Algorithms, Neural Models (Perceptron & ADALINE), and Stochastic Optimization methods.

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