The goal of this project is to develop a deep learning model for classifying news articles into predefined categories such as politics, sports, technology, entertainment, and others. The core architecture uses a Long Short-Term Memory (LSTM) network to learn patterns in the text, while BERT's tokenizer is employed to process the text into a suitable format for input into the model.