This project recommends seven tailored asanas based on a user's health conditions. Additionally, our yoga pose estimator detects incorrect postures for improved form.
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Updated
Jul 15, 2024 - Python
This project recommends seven tailored asanas based on a user's health conditions. Additionally, our yoga pose estimator detects incorrect postures for improved form.
Code to run the ExtRA algorithm for unsupervised topic/aspect extraction on English texts.
Natural language processing of the Wikipedia text (as far English only) with goals to detect contradictory info, and to create a chat bot providing more accurate answers than ChatGPT.
Data Science, Machine Learning, Natural Language Processing, Deep Learning, Quantum Information Processing, Quantum Computing
A comprehensive script for web scraping and NLP analysis, providing detailed insights from extracted articles.
Natural Language Processing
Service robot development for RoboCup @Home OPL
Welcome to the Keyword Processor project! This Streamlit application extracts keywords from text, fetches synonyms and antonyms via API, and displays definitions. It visualizes relationships with dynamic word clouds, providing insights into semantic contexts and linguistic analysis.
Sentiment Intensity Analysis and other Natural Language Processing procedures applied to texts written by the main politic figures of a small town in Barcelona Area (Catalonia). Find the top-positive, top-neutral and top-negative text, person and party. Analyze trends in time; think how speech trends influence popularity before May 2023 elections.
ChunkeyBert is a minimal and easy-to-use keyword extraction technique that leverages BERT embeddings for unsupervised keyphrase extraction from long text documents.
It is a medical chatbot that will provide quick answers to FAQs by setting up rule-based keyword chatbots.
CSIT349 - Applied AI Course Final Project
A resume analyser and creator made in Java.
In today's financial market,news sentiment plays a crucial role in shaping investor behavior and influencing stock prices. By analyzing the sentiment behind stock-related news articles, investors can gain valuable insights to make informed trading decisions.We have performed sentiment analysis of the twitter data based on a whole day to analyse it.
ICLR 2024 论文和开源项目合集
Stock Sentinel is a web app providing stock market investors with sentiment analysis and news aggregation. It uses FinBERT for sentiment analysis and offers stock information, similar stocks suggestions, summaries, and news stories. With real-time insights, it helps users make informed investment decisions. Installation is easy with cloning, depend
Fake news detection using TF-IDF vectorization and LinearSVC
Our project uses a variety of machine learning and deep learning models to forecast supermarkets’ income for the following day based on a multitude of product categories. The main goal of our project is to use feature engineering techniques to improve forecasting accuracy.
Named Entity Recognition with NER Dataset: Our project focuses on implementing Named Entity Recognition (NER) using a specialized NER dataset. Named Entity Recognition is a natural language processing (NLP) task that involves identifying and categorizing entities (such as names of persons, organizations, locations, etc.) within a body of text.
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