Towards application of various machine learning techniques in agriculture

Since the invention of the computer, all available information in every field has been digitized and made available to people who use computer resources. As a result, massive amounts of data are being gener-ated in every domain at an alarming rate. Agriculture is one such area of interest for researchers. Machine learning is the process of extracting useful information from various types of data. The classifi-cation of objects is an important area within the field of data mining, and its application extends to a vari-ety of areas, whether or not in the field of science. Although k-Nearest Neighbor classification is a simple and effective technique, it slows down the classification of each object. Furthermore, the classification's effectiveness suffers as a result of the uneven distribution of training data. The purpose of this paper is to look into the applicability of various machine learning techniques in agriculture. (c) 2021 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the 1st International Con-ference on Computations in Materials and Applied Engineering - 2021.