Topic Modelling for Humans
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Updated
Jun 11, 2024 - Python
Topic Modelling for Humans
Developed a deep learning model utilizing TensorFlow to automate the classification of financial documents. Leveraging a Bidirectional LSTM RNN, we accurately categorize the documents. Our user-friendly Streamlit application ensures high accuracy & efficiency in document management, all deployed on the Hugging Face platform for seamless integration
A very simple framework for state-of-the-art Natural Language Processing (NLP)
Resume Matcher is an open source, free tool to improve your resume. It works by using language models to compare and rank resumes with job descriptions.
An approach exploring and assessing literature-based doc-2-doc recommendations using word2vec combined with doc2vec, and applying it to TREC and RELISH datasets
Sentiment analysis on the IMDB dataset using Bag of Words models (Unigram, Bigram, Trigram, Bigram with TF-IDF) and Sequence to Sequence models (one-hot vectors, word embeddings, pretrained embeddings like GloVe, and transformers with positional embeddings).
Train and evaluate probabilistic word embeddings with Python.
Algorithmic solvers for popular NYT word puzzles
Predicting Drug-Gene Relations via Analogy Tasks with Word Embeddings
Data Science for Psychology: A Book
Using text analytics to understand cultural patterns in philosophical texts. Exploring gender, author, region, and time-period differences, and extracting key philosophical concepts.
Data Fusion on PM 2.5, Weather and News Dataset regarding the city of Patras. Combination of word embeddings and numerical features into Multi Layer Perceptron. News dataset was crawled from thebest.gr, while the PM 2.5 and weather data were kindly given by Post-Doctoral Student Fotis Anagnostopoulos. Continuation of the PROJECT ENIRISST+.
This repo contains my NLP Module Labs
Natural Language Processing | Summer 2023 - Winter 2024
The code powering searchthearxiv.com, a simple semantic search engine for more than 300,000 ML papers on arXiv.
Analysis of Roget's Thesaurus lexicon, using web scraping and machine learning techniques
State-of-the-art count-based word embeddings for low-resource languages with a special focus on historical languages.
EMNLP 2023 Papers: Explore cutting-edge research from EMNLP 2023, the premier conference for advancing empirical methods in natural language processing. Stay updated on the latest in machine learning, deep learning, and natural language processing with code included. ⭐ support NLP!
This repository contains download links to pretrained static word embeddings (word2vec, fastText) in Filipino.
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