This article is a contribution within the Erasmus+ project titled “The Future Lies in Applied Artificial Intelligence(FAAI) and examines research of collected IT specifications of good practices in Area of Artificial Intelligence (AAI). The article describes research conducted, the purpose of which is to find IT specifications of good practices in AI and describe their characteristics, like an area of implementation of the AI solution, the result of processing the data, the source of data, Data processing, and quality, what tools are used for processing data, and others. AAI application cases and the technologies used for implementation are reviewed. The specifics of the data and the applications used are described. The examination of these technologies will provide insight into which ones are favored and provide an overview of what is commonly referred to as “best practices” in this particular domain.The research encompassed a global examination of cases. The analysis of the data offers valuable insights in various directions:<\/p>\n
\uf0a7 Application area of ML\/AI<\/p>\n
\uf0a7 Type of machine learning problems in described good<\/p>\n
practices in Artificial Intelligence<\/p>\n
\uf0a7 Type of models were developed within the projects<\/p>\n
\uf0a7 What is the area of implementation of AI solution<\/p>\n
\uf0a7 Used AI libraries (frameworks).<\/p>\n
\uf0a7 Source of data<\/p>\n
\uf0a7 Data characteristics<\/p>\n
\uf0a7 Tools are used to store data<\/p>\n
\uf0a7 What platform solution is used<\/p>\n
\uf0a7 What type of storage is used.<\/p>\n
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The full paper can be found at:\u00a0https:\/\/ieeexplore.ieee.org\/document\/10316145<\/a><\/p>\n Audio version is available:<\/p>\n