13-Modules-Entity-Name-Single-sentence-Annotation-Data

8178-Chinese-Social-Comments-Events-Annotation-Data

13000000-Groups-Man-Machine-Conversation-Interactive-Text-Data

80000-sets-Multi-domain-Customer-Service-Dialogue-Text-Data

28237-Intent-type-single-sentence-annotation-data

Tools for reshaping text data

The objective of the project is to predict whether a particular tweet, of which the text (occasionally the keyword and the location as well) is provided, indicates a real disaster or not. We use various NLP techniques and classification models for this purpose and objectively compare these models by means of appropriate evaluation metric.

Scrape EDGAR filings from https://www.sec.gov/

⭐️ Contributing as a trainer in a series of AI Workshops (AI-Camp23) ⭐️

Forte is a flexible and powerful ML workflow builder. This is part of the CASL project: http://casl-project.ai/

Systematic Literature Review: Machine Learning Methods in Emotion Classification in Textual Data

Connects to OpenAI, applies Large Language Models (LLMs) & LangChain, and builds a platform to chat with coffee customer review text data using Python. Visualizes text data with R

DupliPy is a quick and easy-to-use package that can handle text formatting and data augmentation tasks for NLP in Python. It now offers support for image augmentation tasks as well.

Large-scale pretrained models for goal-directed dialog

This repository hosts a diverse NLP dataset comprising 1,000 stories spanning 100 genres for comprehensive language understanding tasks.

Text Data: Sentiment Analysis

Summarising text data using NLTK and Gensim libraries

The aim of this work is to predict number of instagram likes. The text vectorization is done using TF-IDF Vectorizer.

Dataset of League of Legends Voice Lines