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Angery at kapitalizmus
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Angery at kapitalizmus
  • Center for Humanities Computing
  • Aarhus, Denmark

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@centre-for-humanities-computing

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x-tabdeveloping/README.md

Márton Kardos

Full time Idiot 💪

Interests:

  • Data Science 📊, NLP 💬
  • Model interpretability and visualization 🎨
  • Optimization, and speed ⚡
  • Bayesian modelling 📚
  • Drums 🎵

Projects:

Turftopic Easy topic modeling with transformer models.
topicwizard Interpret your topic models in a full-fledged interactive framework.
tweetopic Blazing Fast implementations of short-text topic models.
stormtrooper Zero and few shot learning with Large Language Models
embedding-explorer Interactively explore your embeddings with semantic graphs and clustering.
neofuzz Blazing fast fuzzy and semantic text search with the power of machine learning.
OdyCy General Purpose NLP pipelines for Ancient Greek
glovpy Blazing fast GloVe interface for Python wrapping the original C implementation.

Contributions:

embetter Added scikit-learn compatible Gensim encoder models.
MTEB Helped organize the open source effort around MMTEB (Massively Multilingual Text Embedding Benchmark), contributed new tasks and datasets.

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  1. topicwizard topicwizard Public

    Powerful topic model visualization in Python

    Python 105 13

  2. turftopic turftopic Public

    Robust and fast topic models with sentence-transformers.

    Python 35 5

  3. centre-for-humanities-computing/tweetopic centre-for-humanities-computing/tweetopic Public

    Blazing fast topic modelling for short texts.

    Python 31 3

  4. centre-for-humanities-computing/stormtrooper centre-for-humanities-computing/stormtrooper Public

    Zero/few shot learning components for scikit-learn pipelines with LLMs and transformers.

    Python 13 2

  5. neofuzz neofuzz Public

    Blazing fast fuzzy text search for Python.

    Python 38 2

  6. centre-for-humanities-computing/embedding-explorer centre-for-humanities-computing/embedding-explorer Public

    Tools for interactive visual exploration of semantic embeddings.

    Python 29 2