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Name: Persuaide
Type: Organization
Blog: persuai.de
Name: Persuaide
Type: Organization
Blog: persuai.de
Spelling corrector in python
This is the template code to use BERT for sequence lableing and text classification, in order to facilitate BERT for more tasks. Currently, the template code has included conll-2003 named entity identification, Snips Slot Filling and Intent Prediction.
Repository to maintain all my clutter
This repository hosts data and code pour the task of Intent Detection in a few-shot learning setup.
Google Research
Deployed a Keras Intent Recognition model, with blending of codes from Intent Recognition tasks, Kaggle competitions, GRU, LSTM, BERT, and SGD models
Modern spell checking library - accurate, fast, multi-language
The data and code for ACL2020 paper "Logical Natural Language Generation from Open-Domain Tables"
NLPDeep - Deep Learning for using NLP tasks. Focus in quality text.
Summarization, translation, sentiment-analysis, text-generation and more at blazing speed using a T5 version implemented in ONNX.
PoMo: Generating Entity-Specific Post-Modifiers in Context
A pun generator based on the surprisal principle
intent prediction example on spaCy v3
Task 1. Intent detection on Enron email set. We define "intent" here to correspond primarily to the categories "request" and "propose". In some cases, we also apply the positive label to some sentences from the "commit" category if they contain datetime, which makes them useful. Detecting the presence of intent in email is useful in many applications, e.g., machine mediation between human and email. The dataset contains parsed sentences from the email along with their intent (either 'yes' or 'no'). You need to build a learning model which detects whether a given sentence has intent or not. Its a 2-class classification problem. Although its not required you can refer this paper for more information on the dataset : Cohen, William W., Vitor R. Carvalho, and Tom M. Mitchell. "Learning to Classify Email into``Speech Acts''." EMNLP. 2004. Find the train and test dataset in enron.zip. Tip: Try to add feature engineering into your model. Simple baseline with logistic regression gives 71% accuracy.
A web application tagging and retrieval of arguments in text
Change the tense of any text
This is a text formality classifier project that examines how different machine learning models perform in classifying a text as formal or informal. Collaborators: Yonglin Wang, Xiaoyu Lu
TextAttack 🐙 is a Python framework for adversarial attacks, data augmentation, and model training in NLP
Text complexity analyzer based on Coh metrix 3.0
A humorous AI that uses state-of-the-art deep learning to tell jokes
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.