From_my_pen

  Introduction In this blog post, we will explore the implementation of a binary classification model for humor detection using a neural network. In today's world, where humor plays a significant role in entertainment, communication, and even marketing, the ability to detect and understand humor in text has become increasingly important. And humor detection in sentences is an interesting problem that can be solved using machine learning techniques. For this reason, we choose this topic. By accurately detecting humor in sentences, we can automate processes that require humor recognition, such as content moderation, sentiment analysis, and personalization. This automation can save time and resources while providing more engaging and entertaining experiences for users. There were we used 200000 samples in the dataset obtained from Kaggle. The model will be trained on a dataset of sentences labeled with humor tags, and its performance will be evaluated on a test set. The objective of...