TEXT CLASSIFICATION OF ACADEMIC SUBJECT DATA

Abstract

The aim and objective of this project is to develop text classification algorithms to identify the text of four subjects of ll/12th grade. This report explores different techniques used for the classification of text. Various stages including picture preparing like the pre-handling stage, division, and highlight extraction will be examined and talked about.Finally, the end product ofthe algorithms will be written in the software called jupyter notebook by using the languages called python, TensorFlow. This project uses the Artificial Neural Network technique to develop the software. The main advantage of using this technique is that it provides features extraction and detection that is suitable for text recognition. Different models ofthe neural network are discussed Recommendations for future development and conclusions are also included in the report.