saujs Sakarya University Journal of Science 2147-835X Sakarya University 10.16984/saufenbilder.801684 Artificial Intelligence Yapay Zeka Handwritten Digit Recognition Using Machine Learning https://orcid.org/0000-0003-2704-3708 Karakaya Rabia SAKARYA UNIVERSITY https://orcid.org/0000-0002-3682-0831 Kazan Serap SAKARYA UNIVERSITY 02 01 2021 25 1 65 71 09 29 2020 10 30 2020 Copyright © 1997, Sakarya University Journal of Science 1997 Sakarya University Journal of Science

Technology is getting more and more involved in our lives, and so are algorithms. These algorithms speed up work and reduce workload. Especially machine learning algorithms are improving day by day by imitating human behaviours. Handwriting recognition systems are also stand out on this field. In this study, handwriting digit recognition process has been done with algorithms having different working methods. These algorithms are Support Vector Machine (SVM), Decision Tree, Random Forest, Artificial Neural Networks (ANN), K-Nearest Neighbor (KNN) and K- Means Algorithm. The working logic of the handwriting digit recognition process was examined, and the efficiency of different algorithms on the same database was measured. A report was presented by making comparisons on the accuracy.

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