659 Open source projects that are alternatives of or similar to Bert Vocab Builder

Amacımız Türkçe NLP literatüründeki birçok farklı sorunu bir arada çözebilen, eşsiz yaklaşımlar öne süren ve literatürdeki çalışmaların eksiklerini gideren open source bir yazım destekleyicisi/denetleyicisi oluşturmak. Kullanıcıların yazdıkları metinlerdeki yazım yanlışlarını derin öğrenme yaklaşımıyla çözüp aynı zamanda metinlerde anlamsal analizi de gerçekleştirerek bu bağlamda ortaya çıkan yanlışları da fark edip düzeltebilmek.

MixText: Linguistically-Informed Interpolation of Hidden Space for Semi-Supervised Text Classification

A blog which talks about machine learning, deep learning algorithms and the Math. and Machine learning algorithms written from scratch.

Text vectorization tool to outperform TFIDF for classification tasks

SLING - A natural language frame semantics parser

fastNLP: A Modularized and Extensible NLP Framework. Currently still in incubation.

R package for Tokenization, Parts of Speech Tagging, Lemmatization and Dependency Parsing Based on the UDPipe Natural Language Processing Toolkit

This repository contains various ways to calculate sentence vector similarity using NLP models

Python library for Natural Language Preprocessing (NLPre)

本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。

Simple State-of-the-Art BERT-Based Sentence Classification with Keras / TensorFlow 2. Built with HuggingFace's Transformers.

Repository for paper "SWAG: A Large-Scale Adversarial Dataset for Grounded Commonsense Inference"

My completed implementation solutions for CS224N 2019

It is a question-generator model. It takes text and an answer as input and outputs a question.

My (slightly modified) Keras implementation of the Recurrent Convolutional Neural Network (RCNN) described here: http://www.aaai.org/ocs/index.php/AAAI/AAAI15/paper/view/9745.

Paper list of NLP for recommender systems

Web scrapping and related analytics using Python tools

This is a JSON driven angular x based dashboard framework that is inspired by JIRA's dashboard implementation and https://github.com/raulgomis/angular-dashboard-framework

Global-Locally Self-Attentive Dialogue State Tracker

《机器翻译：基础与模型》肖桐 朱靖波 著 - Machine Translation: Foundations and Models

🚪✊Knock Knock: Get notified when your training ends with only two additional lines of code

📖 A curated list of resources dedicated to Natural Language Processing (NLP)

top 1% solution to toxic comment classification challenge on Kaggle.

📅🇨🇳 中国法定节假日数据 自动每日抓取国务院公告

❤️Emotional First Aid Dataset, 心理咨询问答、聊天机器人语料库

Collection of stats, modeling, and data science tools in Python and R.

How to build RNNs and LSTMs from scratch with NumPy.

Cookiecutter API for creating Custom Skills for Azure Search using Python and Docker

Data and software for building the ACL Anthology.

Toolkit for Machine Learning, Natural Language Processing, and Text Generation, in TensorFlow. This is part of the CASL project: http://casl-project.ai/

⚡️A Lightweight NLP Data Loader for All Deep Learning Frameworks in Python

Entity linking framework

🐍 Turkish Language Stemmer for Python

A list of Indonesian NLP resources.

A news recommendation system tailored for user communities

R package providing annotators and a normalized data model for natural language processing

Library to scrape and clean web pages to create massive datasets.

a sklearn wrapper for Google's BERT model

Browse Covid-19 & SARS-CoV-2 Scientific Papers with Transformers 🦠 📖

Julia Implementation of Transformer models

A Curated List of Dataset and Usable Library Resources for NLP in Bahasa Indonesia

DGMs for NLP. A roadmap.

Basic Utilities for PyTorch Natural Language Processing (NLP)

Attention-based multimodal fusion for sentiment analysis

Mishkal is an arabic text vocalization software

A dialogue bot for information access

Topic Modelling for Humans

State of the Art Natural Language Processing

A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.

Collection of software components for natural language processing (NLP) based on the Apache UIMA framework.

PyTorch code for Learning Cooperative Visual Dialog Agents using Deep Reinforcement Learning

A privacy preserving NLP framework

Front-end speech processing aims at extracting proper features from short- term segments of a speech utterance, known as frames. It is a pre-requisite step toward any pattern recognition problem employing speech or audio (e.g., music). Here, we are interesting in voice disorder classification. That is, to develop two-class classifiers, which can discriminate between utterances of a subject suffering from say vocal fold paralysis and utterances of a healthy subject.The mathematical modeling of the speech production system in humans suggests that an all-pole system function is justified [1-3]. As a consequence, linear prediction coefficients (LPCs) constitute a first choice for modeling the magnitute of the short-term spectrum of speech. LPC-derived cepstral coefficients are guaranteed to discriminate between the system (e.g., vocal tract) contribution and that of the excitation. Taking into account the characteristics of the human ear, the mel-frequency cepstral coefficients (MFCCs) emerged as descriptive features of the speech spectral envelope. Similarly to MFCCs, the perceptual linear prediction coefficients (PLPs) could also be derived. The aforementioned sort of speaking tradi- tional features will be tested against agnostic-features extracted by convolu- tive neural networks (CNNs) (e.g., auto-encoders) [4]. The pattern recognition step will be based on Gaussian Mixture Model based classifiers,K-nearest neighbor classifiers, Bayes classifiers, as well as Deep Neural Networks. The Massachussets Eye and Ear Infirmary Dataset (MEEI-Dataset) [5] will be exploited. At the application level, a library for feature extraction and classification in Python will be developed. Credible publicly available resources will be 1used toward achieving our goal, such as KALDI. Comparisons will be made against [6-8].

A simple NLP library allows profiling datasets with one or more text columns. When given a dataset and a column name containing text data, NLP Profiler will return either high-level insights or low-level/granular statistical information about the text in that column.

Vietnamese NLP Toolkit for Node

深度有趣

NeuralQA: A Usable Library for Question Answering on Large Datasets with BERT

Test your HN title against a neural network

Default English stopword lists from many different sources

A frame-semantic parsing system based on a softmax-margin SegRNN.