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.
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Updated
Jun 4, 2024 - Python
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.
Train and evaluate probabilistic word embeddings with Python.
Algorithmic solvers for popular NYT word puzzles
A very simple framework for state-of-the-art Natural Language Processing (NLP)
Topic Modelling for Humans
The code powering searchthearxiv.com, a simple semantic search engine for more than 300,000 ML papers on arXiv.
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!
Top2Vec learns jointly embedded topic, document and word vectors.
Code implementation for our DAS, 2020 paper titled "Fused Text Recogniser and Deep Embeddings Improve Word Recognition and Retrieval"
Deep learning for natural language processing
Tools for training schema-aware Web table embedding for unsupervised and supervised machine learning on tabular data
An approach exploring and assessing literature-based doc-2-doc recommendations using word2vec combined with doc2vec, and applying it to TREC and RELISH datasets
WEFE: The Word Embeddings Fairness Evaluation Framework. WEFE is a framework that standardizes the bias measurement and mitigation in Word Embeddings models. Please feel welcome to open an issue in case you have any questions or a pull request if you want to contribute to the project!
Opensearch + Openai + FastAPI + Word Embeddings demo
Multi-Relational Hyperbolic Word Embeddings from Natural Language Definitions
Beautiful visualizations of how language differs among document types.
A package for reading/writing files containing pre-trained word embeddings and building "embedding matrices".
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