Extracting intents and entities using rasa-nlu and training on a custom set of utterances
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Updated
Sep 11, 2018 - JavaScript
Extracting intents and entities using rasa-nlu and training on a custom set of utterances
An Open-Source Package for Universal Extraction (UE)
Detection of email intent as "yes" or "no".
Machine Learning Behind AI Smart Assistant in Smart Home
Find outlier/anomaly for multi-class intents using Snips NLU
Intent classification is the automatic categorization of text data based on customer goals. It is known to be a complex problem in NLP. Sequence Labelling aims to classify each token (word) in a class space C. This project addresses these two problem statements by covering the basic concepts of NLP to advanced ones. For instance, linguistics ana…
Dialog agent for handling task oriented chat
An intent recognition library.
Final project for class Data Science Lab: process and methods; Politecnico di Torino (2022/2023); 1st year of Master's Degree in Data Science and Engineering coursework.
Implementation of 3 different models for joint intent classification and slot filling including two RNN-based model and a BERT-based one
AI-powered speech-to-text and text-to-speech platform with intelligent analysis using Deepgram. Features sentiment analysis, topic detection, intent recognition, and multiple voice personas.
BERT for joint intent classification and slot filling
A multilingual intent classficiation service
对话机器人,闲聊机器人,chatbot,faqbot,taskbot,FAQ,任务型,问答型,事实型,知识图谱,对话,机器人
AI Chatbot with Intent Classification A modern chatbot app powered by TensorFlow.js for client-side intent recognition. Designed for fast, lightweight performance, featuring dark mode support, animated SVG robot logo, and a responsive chat interface with typing indicators all running entirely in the browser with no server-side dependencies.
A library for Transformers-based Vietnamese Natural Language Understanding (NLU).
Python scripts to extract Slack messages, and classify their intent using OpenAI's GPT-4 API
This project uses a Bidirectional LSTM model to classify flight-related queries into 8 intents. Trained on the ATIS dataset, it achieved 97% test accuracy and is ideal for travel-related chatbots.
A machine learning system for classifying customer intents in Vietnamese conversations, designed for e-commerce customer service applications.
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