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Over the past decade, machine learning methods have given us driverless cars,voice recognition, effective web search, and a much better understanding of thehuman genome. Machine learning is so common today that it is used dozens oftimes a day, possibly unknowingly. Trying to teach a machine some processes orsome situations can make them predict some results that are difficult topredict by the human brain. These methods also help us do some operations thatare often impossible or difficult to do with human activities in a short time.For these reasons, machine learning is so important today. In this study, twodifferent machine learning methods were combined. In order to solve areal-world problem, the manuscript documents were first transferred to thecomputer and then classified. We used three basic methods to realize the wholeprocess. Handwriting or printed documents have been digitalized by a scanner ordigital camera. These documents have been processed with two different OpticalCharacter Recognition (OCR) operation. After that generated texts areclassified by using Naive Bayes algorithm. All project was programmed inMicrosoft Visual Studio 12 platform on Windows operating system. C# programminglanguage was used for all parts of the study. Also, some prepared codes andDLLs were used.

Classification of Documents Extracted from Images with Optical Character Recognition Methods