A Guide to Genetic ‘Learning’ Algorithms for Optimization

In a broader mathematical or computational perspective, an optimization problem is defined as a problem of finding the best solution from all feasible solutions. In terms of Machine Learning and Artificial Intelligence, two significant algorithms that perform these tasks are Reinforcement Learning and Genetic Algorithms. They serve the purpose of finding the ‘best fit’ solutions from a range of possible solutions for a given problem statement. In the article that follows below, we will be working closely on these algorithms and will see their implementation in action on an Image Processing problem. <a href="https://towardsdatascience.com/a-guide-to-genetic-learning-algorithms-for-optimization-e1067cdc77e7">Website</a>