659 Open source projects that are alternatives of or similar to Lineflow

Ruby SDK for Dialogflow

This repository is for my students of Udemy. You can find all lecture codes along with mentioned files for reading in here. So, feel free to clone it and if you have any problem just raise a question.

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

NLP progress in Fintech. A repository to track the progress in Natural Language Processing (NLP) related to the domain of Finance, including the datasets, papers, and current state-of-the-art results for the most popular tasks.

Official Python client for the MonkeyLearn API. Build and consume machine learning models for language processing from your Python apps.

SLING - A natural language frame semantics parser

Türkiye'de yapılan derin öğrenme (deep learning) ve makine öğrenmesi (machine learning) çalışmalarının derlendiği sayfa.

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

互联网大厂面试经验

Important paper implementations for Question Answering using PyTorch

The CRF Layer was implemented by using Chainer 2.0. Please see more details here: https://createmomo.github.io/2017/09/12/CRF_Layer_on_the_Top_of_BiLSTM_1/

📚Survey of previous research and related works on machine learning (especially Deep Learning) in Japanese

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

👩‍🏫 Advanced NLP with spaCy: A free online course

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

Japanese negative positive classification.日本語文書のネガポジを判定。

📅🇨🇳 中国法定节假日数据 自动每日抓取国务院公告

A JavaFX based desktop search application.

Paper list of NLP for recommender systems

R client for the Google Translation API, Google Cloud Natural Language API and Google Cloud Speech API

Python wrapper for evaluating summarization quality by ROUGE package

Worth-reading papers and related awesome resources on aspect-based sentiment analysis (ABSA). 值得一读的方面级情感分析论文与相关资源集合

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

Pre-Trained Models for ToD-BERT

QANTA Quiz Bowl AI

A Library to parse natural language in pure Clojure and ClojureScript

Data augmentation for NLP

Topic Modelling for Humans

Chinese Biomedical Language Understanding Evaluation benchmark (ChineseBLUE)

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

💙 Emoji handling and meta data for spaCy with custom extension attributes

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

A natural language date parser in Swift (ported from chrono.js)

A news recommendation system tailored for user communities

Cantonese Linguistics and NLP in Python

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

Implementation of the paper Tree Transformer

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

A Ruby natural language processor.

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].

Character-level Convolutional Neural Networks for text classification in PyTorch

🐍 Turkish Language Stemmer for Python

阿里天池首届中文NL2SQL挑战赛top6

How to build RNNs and LSTMs from scratch with NumPy.

Machine learning models to automatically summarise scientific papers

Basic Utilities for PyTorch Natural Language Processing (NLP)

This repository contains landmark research papers in Natural Language Processing that came out in this century.

基于深度学习的自然语言处理库

Implementation of Siamese Neural Networks built upon multihead attention mechanism for text semantic similarity task.

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

Code for the ACL 2018 paper "Neural Document Summarization by Jointly Learning to Score and Select Sentences"

This repo contains my coursework, assignments, and Slides for Natural Language Processing Specialization by deeplearning.ai on Coursera

Stanford NLP group's shared Python tools.

Mishkal is an arabic text vocalization software

Examine two sentences and determine whether they have the same meaning.

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

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.

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

Python library for Natural Language Preprocessing (NLPre)

Automatically extract chemical information from scientific documents