A Deep Learning-Based Approach for Named Entity Recognition on Commercial Receipts

Repository for the free online book Oddly Satisfying Deep Learning from Scratch (link below!)

Twitter Sentiment analysis using RNS like LSTMs, GRUs and enhancing the performance with ELMo embeddings and a self-attention model

Context-Aware Semantic Similarity Measurement for Unsupervised Word Sense Disambiguation

Apply Bi-LSTM with self-attention, attached CRF for Named Entity Recognition.

An Empirical Evaluation of Word Embedding Models for Subjectivity Analysis Tasks

Developed an ensemble of state of the art transformer architectures to enhance accuracies on binary classification

Flask based application using to detect depression for transcripts of interviews from patients

pretrained transformer and embeddings language models

Python code to make the best use of the internet.

This GitHub repository contains implementations of three popular word embedding techniques: Singular Value Decomposition (SVD), Continuous Bag of Words (CBOW), and Embeddings from Language Models (ELMO). Word embeddings are a fundamental component of natural language processing and are essential for various text-based machine learning tasks.

An implementation of ELMo embeddings using PyTorch, featuring stacked Bi-LSTMs for contextualized word representations. Pretrained on bidirectional language modeling and evaluated on the AG News dataset for text classification, achieving metrics like accuracy, F1, and precision.

This repository contains implementations of ELMo (Embeddings from Language Models) models trained on a news dataset. Additionally, it includes a classification task using ELMo embeddings.

This project aims to implement various word embedding methods.

Sentimental Analysis

Intro to NLP Assignments on Word2vec, Smoothing, ELMO, POS Tagging

한국어 임베딩 책을 바탕으로 임베딩 모델에 대한 공부

This repo provides a comprehensive overview of ELMo (Embeddings from Language Models), a deep contextualized word representation model,