Enhanced Method for News Headline Classification Using Deep Learning

In a world where human communication is paramount, the complexities of language go beyond spoken words. This research study performs news headline classification, harnessing machine learning's power to detect the complex news headlines. This study intends to create a model capable of identifying the underlying patterns within headlines and categorizing them into distinct groups. Through rigorous experimentation and fine-tuning with the help of Convolutional Neural Network (CNN) along with Long Short-Term Memory (LSTM), where remarkable results have been achieved with an overall accuracy of 90%. This model combines the knowledge of multiple machine learning algorithms to perform exceptionally well in headline classification just like diverse models are merged to obtain higher performance. It is useful for making sense of and managing the information available in the digital age.