This project provides 100+ Chinese Word Vectors (embeddings) trained with different representations (dense and sparse), context features (word, ngram, character, and more), and corpora. One can easily ...

Word Embedding (Python) is a technique to convert words into a vector representation. Computers cannot directly understand words/text as they only deal with numbers. So we need to convert words into ...

In this video, we will about training word embeddings by writing a python code. So we will write a python code to train word embeddings. To train word embeddings, we need to solve a fake problem. This ...

"Gender ideology" is a nonsense term, meant to obscure meaning and frighten people. His lies also depend on people not reading his various anti-trans executive orders. It's not just that these orders ...

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.

Code embeddings are a transformative way to represent code snippets as dense vectors in a continuous space. These embeddings capture the semantic and functional relationships between code snippets, ...

Abstract: Word embeddings play a crucial role in various NLP-based downstream tasks by mapping words onto a relevant space, primarily determined by their co-occurrences and similarities within a given ...

Abstract: Query by example spoken term detection (QbE-STD) is a popular keyword detection method in the absence of speech resources. It can build a keyword query system with decent performance when ...