1314 Open source projects that are alternatives of or similar to Fastrtext

中文长文本分类、短句子分类、多标签分类、两句子相似度（Chinese Text Classification of Keras NLP, multi-label classify, or sentence classify, long or short），字词句向量嵌入层（embeddings）和网络层（graph）构建基类，FastText，TextCNN，CharCNN，TextRNN, RCNN, DCNN, DPCNN, VDCNN, CRNN, Bert, Xlnet, Albert, Attention, DeepMoji, HAN, 胶囊网络-CapsuleNet, Transformer-encode, Seq2seq, SWEM, LEAM, TextGCN

Data augmentation for NLP, presented at EMNLP 2019

Visualize word embeddings of a vocabulary in TensorBoard, including the neighbors

FastText for Node.js

all kinds of text classification models and more with deep learning

A fast, efficient universal vector embedding utility package.

An experiment about re-implementing supervised learning models based on shallow neural network approaches (e.g. fastText) with some additional exclusive features and nice API. Written in Python and fully compatible with Scikit-learn.

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Sentiment analysis of tweets in Russian using Convolutional Neural Networks (CNN) with Word2Vec embeddings.

Sentiment Analysis: Deep Bi-LSTM+attention model

R package to Embed All the Things! using StarSpace

Text classification meets word embeddings.

Relation Classification - SEMEVAL 2010 task 8 dataset

Mixing Dirichlet Topic Models and Word Embeddings to Make lda2vec from this paper https://arxiv.org/abs/1605.02019

Use machine learning in AppInventor, with easy training using text, images, or numbers through the Machine Learning for Kids website.

Text Classification in Turkish Texts with Bert

Multi-class text categorization using state-of-the-art pre-trained contextualized language models, e.g. BERT

Text Similarity Applied to resume, to compare Resumes with Job Descriptions and create a score to rank them. Similar to an ATS.

Lbl2Vec learns jointly embedded label, document and word vectors to retrieve documents with predefined topics from an unlabeled document corpus.

Persian sentiment analysis ( آناکاوی سهش های فارسی | تحلیل احساسات فارسی )

BioWordVec & BioSentVec: pre-trained embeddings for biomedical words and sentences

🗣️ Tool to generate adversarial text examples and test machine learning models against them

Classify Kaggle San Francisco Crime Description into 39 classes. Build the model with CNN, RNN (GRU and LSTM) and Word Embeddings on Tensorflow.

A Modern C++ Data Sciences Toolkit

A tool for learning vector representations of words and entities from Wikipedia

Pre-training of Deep Bidirectional Transformers for Language Understanding: pre-train TextCNN

Tools for shrinking fastText models (in gensim format)

Named-Entity Recognition in Persian Language

Deep-learning model presented in "DataStories at SemEval-2017 Task 6: Siamese LSTM with Attention for Humorous Text Comparison".

NLP tutorial

Google News and Leo Tolstoy: Visualizing Word2Vec Word Embeddings using t-SNE.

A text analysis application for performing common NLP tasks through a web dashboard interface and an API

Implementing nlp papers relevant to classification with PyTorch, gluonnlp

Exploring the simple sentence similarity measurements using word embeddings

Text processing library for sentiment analysis and related tasks

Sample code for training Word2Vec and FastText using wiki corpus and their pretrained word embedding..

Documents, papers and codes related to Natural Language Processing, including Topic Model, Word Embedding, Named Entity Recognition, Text Classificatin, Text Generation, Text Similarity, Machine Translation)，etc. All codes are implemented intensorflow 2.0.

Library for fast text representation and extreme classification.

Nodejs binding for fasttext representation and classification.

This case study shows how to create a model for text analysis and classification and deploy it as a web service in Azure cloud in order to automatically classify support tickets. This project is a proof of concept made by Microsoft (Commercial Software Engineering team) in collaboration with Endava http://endava.com/en

CNN-RNN中文文本分类，基于TensorFlow

PyTorch implementation of a deep metric learning technique called "Magnet Loss" from Facebook AI Research (FAIR) in ICLR 2016.

Classify Kaggle Consumer Finance Complaints into 11 classes. Build the model with CNN (Convolutional Neural Network) and Word Embeddings on Tensorflow.

Fast word vectors with little memory usage in Python

Text classification models implemented in Keras, including: FastText, TextCNN, TextRNN, TextBiRNN, TextAttBiRNN, HAN, RCNN, RCNNVariant, etc.

Compute Sentence Embeddings Fast!

Ipython Notebooks for solving problems like classification, segmentation, generation using latest Deep learning algorithms on different publicly available text and image data-sets.

Implementation of State-of-the-art Text Classification Models in Pytorch

Chinese Question Classifier (Keras Implementation) on BQuLD

Dict2vec is a framework to learn word embeddings using lexical dictionaries.

All kinds of neural text classifiers implemented by Keras

A Python interface for Facebook fastText

Machine learning based text classification in JavaScript using n-grams and cosine similarity

Arabic support for textblob

Repo for Applied Text Mining in Python (coursera) by University of Michigan

Deep-Atrous-CNN-Text-Network: End-to-end word level model for sentiment analysis and other text classifications

Telegram Data Clustering contest solution by Mindful Squirrel

Fake News Detection in Python

Implementing nlp papers relevant to classification with PyTorch, gluonnlp

RMDL: Random Multimodel Deep Learning for Classification