News Article Topic Classification Using Embeddings

The rate at which data is produced has increased dramatically in recent days. Without a suitable category or tag, having a lot of data is merely useless information. The consumer may quickly find the content they’re looking for and search for older news stories with ease when news items are properly categorized or classified. The classification of News Article Topics into proper categories aids in many tasks such as finding older data in a faster way, useful organization of data, enabling quick fetching of required data, etc. The proposed system analyses the Antonio Gulli’s (AG) News Classification Dataset using different embeddings. The proposed model also experiments with different types of Machine Learning and Deep Learning Classifiers for classifying the embeddings.