Algorithms for Machine Learning with Orange System

Emphasized is the need for new approaches and solutions for forming of increased information awareness, knowledge and competencies in the present and future generations to use the possibilities of emerging technolo-gies for technological breakthroughs. The article presents basic machine learning tools of both types: supervised learning, which trains a model on known input and output data and predicts future results, and unsupervised learning, which finds hidden patterns or inherent structures in the input data. Algorithms for the processes of creating an information flow when applying the tools of the Orange system, which can be used for research, analysis and training, are formulated. Experiments related to smart crop production and analyses with different classifi-cation, regression and clustering algorithms. The results show that the formulated solutions can be successfully used for different tasks and can be adapted to new technologies and applications.