Sarcasm detection in comments from Reddit
-
Updated
Jul 18, 2018 - Jupyter Notebook
Sarcasm detection in comments from Reddit
NLP | Zero to Hero Course Tensorflow| Text classification Model to understand sentiments in text.
Sarcasm Detection using NLP techniques
Multilingual sarcasm detector for detecting sarcasm from news article titles
Repository of the Project 5: Sarcasm detection in sentences using neural networks, word embeddings and padding. Performing data cleaning & preparation, data visualization and creating a user input as well as a small website using Streamlit.
Text Mining and Sarcasm Detection on News Data
A project consisting of analysis of sarcasm in text using Natural Language Processing techniques. It highlights the importance of context and punctuation in sarcasm detection. Different deep learning models are applied and compared to get the best accuracy in sarcasm detection.
Sarcasm detection model, trained on Sarcasm on Reddit Dataset.
This projects have been my learning while working on tensorflow on how to create models using tensorflow and solve nlp problems
Transfer Learning for News Headline Sarcasm Detection Using BERT Based Supervised Fine-Tuning
AI model which checks whether a given text is sarcastic or not?
My projects and practices on various segments of machine learning and deep learning.
A neural network trained for detecting sarcasm in reddit comments. This project was implemented in python using jupyter notebook for the applied machine learning algorithm course at KIT. Everything was developed together with Philip Schröder as a two man project.
Detecting sarcasm in texts
Developing a Sarcasm Detection Solution using Machine Learning and Deep Learning Approaches
Detect Sarcasm in headlines of news articles 🤓
Sarcasm detection in textual data using different feature embeddings and models.
Add a description, image, and links to the sarcasm-detection topic page so that developers can more easily learn about it.
To associate your repository with the sarcasm-detection topic, visit your repo's landing page and select "manage topics."