BnVec: Towards the Development of Word Embedding for Bangla Language Processing

Progression in machine learning and statistical inference are facilitating the advancement of domains like computer vision, natural language processing (NLP), automation & robotics, so on. Among different persuasive improvements NLP, word embedding is one most used revolutionary techniques. In this paper, we manifest an open-source library for Bangla extraction systems named BnVec which expects to furnish NLP research community by utilization some incredible The splitted up into two parts, first suitable defined class embed words with access six popular schemes (CountVectorizer, TF-IDF, Hash Vectorizer, Word2vec, fastText, Glove). other based on pre-trained distributed system GloVe. models have been built collecting content from newspaper, social media, wiki articles. total number tokens build exceeds 395,289,960. paper additionally depicts performance these various hyper-parameter tuning then analyzes results.