Abstract :

The words "artificial intelligence" (AI) and "machine learning" (ML) have entered common use. AI is using a wide variety of algorithms, including ML. Nevertheless, inexperienced users often employ each of these expressions alone. Improving the substance of AI and ML projects and giving first time contributors a chance to take on new challenges may be achieved via analyzing and understanding their relevance and function. Analyses of ML and AI projects hosted on GitHub, both quantitative and qualitative, constitute the bulk of this work. In order to back up the analysis, three research questions (RQ) have been generated. A number of factors, including programming languages, forked repositories, and commits, are taken into account in the study. Open-Source Projects, First-Time Contributors, Quantitative and Qualitative Analysis, Machine Learning, GitHub