Question answering (QA) is a computer science discipline within the fields of information retrieval and natural language processing (NLP), which is concerned with building systems that automatically answer questions posed by humans in a natural language.

Deep learning (DL) approaches use various processing layers to learn hierarchical representations of data. Recently, many methods and designs of natural language processing (NLP) models have shown significant development, especially in text mining and analysis. For learning vector-space representations of text, there are famous models like Word2…

This repository contains data and BioBert based NER model monologg/biobert_v1.1_pubmed from community-uploaded Hugging Face models for detecting entities such as chemical and disease.

Arabic Dialect Identification between 18 country-level Arabic dialects using QADI dataset and pretrained language model AraBERT

Sentiment analysis is the use of natural language processing, text analysis, computational linguistics, and biometrics to systematically identify, extract, quantify, and study affective states and subjective information. So, in this application, we are asking a YouTuber to enter the channel id and a particular timeline. By using the channel id a…

Fine-tuning a BERT model using Ktrain | Transfer Learning NLP | Fine Tune Bert For Text Classification

Machine learning (ML) solution that review end-user license agreements (EULA) for terms and conditions that are unacceptable to the government

12th place (top 4%) solution for Shopee Code League 2020 - Sentiment Analysis

Twitter has become an important communication channel in times of emergency. The ubiquitousness of smartphones enables people to announce an emergency they’re observing in real-time. Because of this, more agencies are interested in programatically monitoring Twitter (i.e. disaster relief organizations and news agencies). But, it’s not always cle…

Topic modeling in python and visualization of data using amazon food reviews dataset,20_Newsgroup dataset

Political Fake News

Part of data repository for thesis/skripsi titled: "Assessment Study on ktrain Library for Text Processing"

Twitter Sentiment Analysis using various models

Automated & Augmented ML Toolbox for Image Classification

BERT is a Transformer-based machine learning technique for natural language processing (NLP) pre-training developed by Google.

Build a multi-headed model that’s capable of detecting different types of of toxicity like threats, obscenity, insults, and identity-based hate.

Ref: https://github.com/tarcisio-marinho/A-Deep-Learning-Approach-to-Web-Application-Firewall

Simple, Pythonic, text processing--Sentiment analysis, part-of-speech tagging, noun phrase extraction, translation, and more.

Emotion analysis of English tweets using machine learning approach.