Sentence Segementor basically helps in classifying sentence boundaries using Named Entity Recognition method. The classifier has been found useful in application like machine translation, sentence classification, NMT etc.

Our project aims at classifying the given news articles as fake or true based on the content using few-shot learning models with fewer data.

Comparison of multimodal models for Emotion Detection on IEMOCAP

This project uses machine learning to categorize and prioritize airline user tweets based on content and sentiment. The goal is to reduce airlines' workload and provide personalized, empathetic responses to users. By training a sentiment analysis model, airlines can better understand customers' needs and improve their overall service on Twitter.

text-generator-Krisko-lyrics

Predictive and Prescriptive Analytics Using LSTM techniques

Deep Learning Based NER Tool for Turkish with BiLSTM, BiGRU, fine-tuned BERT models

A simple many-to-one string generating Bidirectional LSTM using pytorch

Hotel Review Classifier with BiLSTM

A Reverse Dictionary using BERT, and a new high quality Dataset

Codebase for SiMiD model

Exploring Advanced Models for Time Series-Based Weather Forecasting in Bangladesh: A Comparative Analysis of ARIMA, SARIMA, FB-Prophet, LSTM and BiLSTM Models

This research investigates flight delay trends, examining departure time, airline, and airport factors. Regression machine learning meth- ods are utilized to predict delay contributions from various sources. Time-series models, including LSTM, Hybrid LSTM, and Bi-LSTM, are compared with baseline regression models such as Multiple Regression, Decisi

情感分类（六分类）

PoS Tagging with Bidirectional Long Short-Term Memory Models

toxic comment classification using various model

Context-dependent model pipeline (BERT-CNN-BiLSTM) for Sentiment Analysis on 2 different datasets.

An experiment conducted on Twitter, using Bag of Words and BiLSTM algorithms, focus solving three questions.