Word Embeddings
Showing 18 of 18 projects
A simple Python framework for state-of-the-art natural language processing (NLP) tasks like named entity recognition and sentiment analysis.
A simple Python framework for state-of-the-art natural language processing (NLP) tasks like named entity recognition and sentiment analysis.
A command-line tool that performs semantic searches on text using word embeddings to find words with similar meaning to the query.
An efficient R package for text analysis and NLP with fast vectorization, topic modeling, and word embeddings.
Catalyst is a high-performance C# NLP library inspired by spaCy, offering pre-trained models, entity recognition, and embedding training.
A Go library implementing word embedding models (Word2Vec, GloVe, LexVec) from scratch with CLI and SDK.
A curated list of resources for Natural Language Processing (NLP) in Polish, including datasets, models, and tools.
A TensorFlow implementation of fastText for embedding-based text classification with support for character ngrams and distributed training.
A community-curated list of NLP tools, libraries, datasets, and resources across speech processing, text analysis, and machine translation.
A Julia package for loading pretrained word embeddings like Word2Vec, FastText, and GloVe.
A Ruby wrapper for the spaCy NLP library via PyCall, enabling tokenization, POS tagging, NER, and OpenAI integration.
A Go package for reading word2vec vectors and performing similarity searches and analogies.
A native Objective-C framework for experimenting with neural networks and natural language processing on macOS and iOS.
A German ELMo deep contextualized word representation model trained on a specialized German Wikipedia text corpus for NLP tasks.
A scikit-learn pipeline implementing the projection layer of Self-Governing Neural Networks (SGNN) using character n-grams and random hashing.
A Python command-line tool for encoding text sequences into vector-of-vector representations using word embeddings.
Generate word embedding vectors from text files using the Swivel algorithm on IBM Watson Machine Learning.
A command-line tool that finds Typo-Bridges—typos that could plausibly be two different intended words—to explore ambiguity and intentional inclusion in text.
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