659 Open source projects that are alternatives of or similar to Turkish Stemmer Python

🧬 A JupyterLab extension for annotating data with Prodigy

Typing Assistant provides the ability to autocomplete words and suggests predictions for the next word. This makes typing faster, more intelligent and reduces effort.

Cantonese Linguistics and NLP in Python

Code to reproduce results in our ACL 2018 paper "Did the Model Understand the Question?"

Botfuel SDK to build highly conversational chatbots

An implementation of the NAACL 2018 paper "Punny Captions: Witty Wordplay in Image Descriptions".

NLP, before and after spaCy

DeepLearning.AI TensorFlow Developer Professional Certificate Specialization

A tutorial on how to implement models for part-of-speech tagging using PyTorch and TorchText.

REx: Relation Extraction. Modernized re-write of the code in the master's thesis: "Relation Extraction using Distant Supervision, SVMs, and Probabalistic First-Order Logic"

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

Pre-trained subword embeddings in 275 languages, based on Byte-Pair Encoding (BPE)

A comparison tool of Japanese tokenizers

This is an implementation of the paper written by Yuhua Li, David McLean, Zuhair A. Bandar, James D. O’Shea, and Keeley Crockett

Character-based word embeddings model based on RNN for handling real world texts

Overview of NLP tools and techniques in python

Multitask Deep Learning for Sentiment Analysis using Character-Level Language Model, Bi-LSTMs for POS Tag, Chunking and Unsupervised Dependency Parsing. Inspired by this great article https://arxiv.org/abs/1611.01587

[DEPRECATED] Ultimate Node.JS SDK for api.ai

Implementation of the paper Tree Transformer

Python Keyphrase Extraction module

🏖TagEditor - Annotation tool for spaCy

A collection of research on knowledge graphs

RASA chatbot use case boilerplate

Notes on Deep Reinforcement Learning for Natural Language Processing papers

Abydos NLP/IR library for Python

🛸 Use pretrained transformers like BERT, XLNet and GPT-2 in spaCy

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].

Curated List: Practical Natural Language Processing done in Ruby

A PureScript, browser-based implementation of LDA topic modeling.

Code for the paper "BIOLITMAP: a web-based geolocated and temporal visualization of the evolution of bioinformatics publications" in Oxford Bioinformatics.

PyTorch implementation of latent space reinforcement learning for E2E dialog published at NAACL 2019. It is released by Tiancheng Zhao (Tony) from Dialog Research Center, LTI, CMU

NeuralParser is a very simple to use dependency parser, based on the Latent Syntactic Structure encoding.

📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.

Source code and data for the paper "Towards String-to-Tree Neural Machine Translation"

A Ruby natural language processor.

Awesome Artificial Intelligence, Machine Learning and Deep Learning as we learn it. Study notes and a curated list of awesome resources of such topics.

Forte is a flexible and powerful NLP builder FOR TExt. This is part of the CASL project: http://casl-project.ai/

⚡ Automatically decrypt encryptions without knowing the key or cipher, decode encodings, and crack hashes ⚡

Evaluation code for various unsupervised automated metrics for Natural Language Generation.

meProp: Sparsified Back Propagation for Accelerated Deep Learning (ICML 2017)

PORORO: Platform Of neuRal mOdels for natuRal language prOcessing

Basic Utilities for PyTorch Natural Language Processing (NLP)

😇A pyTorch implementation of the DeepMoji model: state-of-the-art deep learning model for analyzing sentiment, emotion, sarcasm etc

Pytorch implementation of "Graph Convolutional Networks for Text Classification"

Quiz & Assignment of Coursera

Machine Learning University: Accelerated Natural Language Processing Class

Unsupervised text tokenizer focused on computational efficiency

Implementation of the multi feed-forward network architecture by Parikh et al. (2016) for Natural Language Inference.

Fast vectorization, topic modeling, distances and GloVe word embeddings in R.

Character-level Convolutional Neural Networks for text classification in PyTorch

A linux based Virtual assistant on Artificial Intelligence in C

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.

Paper list of NLP for recommender systems

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

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

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/

Helsinki Prosody Corpus and A System for Predicting Prosodic Prominence from Text

UA-GEC: Grammatical Error Correction and Fluency Corpus for the Ukrainian Language

Corpus of Annual Reports in Japan