Machine learning focuses on the development of computer programs that can access data and use it to learn for themselves. Genetic mapping is based on the use of Genetic Techniques to construct maps showing the positions of genes and other sequence features on genome. The early applications of machine learning to population genetics demonstrate that they outperform traditional approaches. Potentially important disease biomarkers have been revealed by the use of machine learning methods on gene expression data, where algorithms learn to differentiate between different disease phenotypes. Genetic testing can be considered as the perfect field for machine learning applications in many ways, considering the enormous amount of data that these programs need to contend with.