Machine learning-focused educational web portal

The main goal of this thesis is to create a machine learning-focused educational web portal with interactive examples and publicly available source code containing both the interactive examples and code of the portal. The thesis is structured into two parts. The theoretical part contains explanations of two chosen machine learning techniques, genetic algorithms, and neural networks. Both explanations are suited for readers without previous knowledge in the machine learning field. However, for both techniques a basic understanding of programming concepts is necessary. On top of that, neural networks require basic understanding of calculus, namely derivates. The practical part of the thesis describes the MMSP software development methodology used for the development of the portal. Rest of the practical part follows the development process of the portal and interactive examples using mentioned methodology. The development process is covered from the selection of tools to publishing the portal on the internet. Texts from the theoretical part are used in tutorials present on the web portal. The conclusion of this thesis provides a summary of the whole development process and propose further work on the portal, namely the graphical appearance and more machine learning techniques.