Embeddings and Word2Vec
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Updated
Jul 9, 2017 - Jupyter Notebook
Embeddings and Word2Vec
Convolution Neural Network for classification of semantic relations in a sentence
Generate new Simpson's TV scripts using neural network
Slides from various seminars held during grad school and beyond
Implementation of word2vec in PyTorch
My master project at UofL: End-to-End learning framework for circular RNA classification from other long non-coding RNA using multimodal deep learning
End-to-end learning framework for circular RNA classification from other long non-coding RNAs using multi-modal deep learning.
word embedding resources for sentiment classification
Machine translation is the task of converting one language to other. Unlike the traditional phrase-based translation system which consists of many small sub-components that are tuned separately, neural machine translation attempts to build and train a single, large neural network that reads a sentence and outputs a correct translation.
Place2Vec ground truth dataset
A collection of Natural Language Processing challenges and my solutions for them that include traditional methods and deep learning.
This repository contains code for learning word2vec embeddings using skip-gram model
Reference implementation of the paper "Word Embeddings for Entity-annotated Texts"
Transportation analysis with social social media data
Hate speech detection from code-mixed Hindi-English tweets using deep learning models. This project reports an increment to the state-of-the-art in hate speech detection for English-Hindi code-mixed tweets. The models result in an improvement of about 12% in F-score over a past work that used statistical classifiers.
Sense Embeddings for Word and Relational Similarity.
This repository is about producing nballs embeddings for Hindi language which takes into account the word embeddings and hypernym relations among the words.
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