This study investigates the comparison of Machine Learning model and Neural Network model in Uzbek language text classification problem. In this study, the dataset aligned into 11 classes which extracted from the project of text classification dataset for Uzbek language. The Machine Learning model gained 94% accuracy, while the Neural Network model achieved slightly better result with an accuracy rate of 95%. This research highlights the significance of model selection in This research highlights the importance of model selection and suggests neural networks’ promise for Uzbek
NLP tasks.