Machine Learning/Artificial Intelligence Techniques and Applications in the Domain of Data Science

Abstract

Digitalization has revolutionized data science, allowing researchers and organizations to extract meaning from complex data sets and uncover actionable insights with the use of Artificial intelligence and machine learning. Several studies suggested the potential of connecting artificial intelligence with data science could have in many fields and areas. Therefore, the purpose of the thesis is to uncover possibilities of contexts to design a platform which could support data science needs with the use of machine learning standards. Therefore, several questions were asked to anticipated uses of similar areas, standards used by them, issues faced by them, and steps taken to achieve them. The research was approached as qualitative research and it was handled theoretically to come up with a proper design which could support the main intention of the project. The document addressed relative concepts, standards, development methodologies and required technologies which assisted to form a theoretical structure to support arguments to highlight the importance of having use of Artificial intelligence and data science. In the end, a concise amount of information was gathered to support and evidently prove a correlation between Artificial Intelligence and Data Science while demonstrating it using existing examples and proposed design from this document. Therefore, all collective information supports its influence which can have on a broader area and those chances can be used for further improvements in the field as I suggested it use in research and development from this document.