305 Open source projects that are alternatives of or similar to Embeddingsviz

A fast, efficient universal vector embedding utility package.

Deep-learning model presented in "DataStories at SemEval-2017 Task 4: Deep LSTM with Attention for Message-level and Topic-based Sentiment Analysis".

R wrapper for fastText

finalfusion embeddings in Rust

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

Fast word vectors with little memory usage in Python

Exploring the simple sentence similarity measurements using word embeddings

One-Stop Solution to encode sentence to fixed length vectors from various embedding techniques

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

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

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

Tutorials on getting started with PyTorch and TorchText for sentiment analysis.

Compute Sentence Embeddings Fast!

🎨 🎨NLP 自然语言处理教程 🎨🎨 https://dataxujing.github.io/NLP-paper/

Code for "Effective Dimensionality Reduction for Word Embeddings".

FastText for Node.js

Topic Modelling for Humans

Tools for shrinking fastText models (in gensim format)

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

Taking a pretrained GloVe model, and using it as a TensorFlow embedding weight layer **inside the GPU**. Therefore, you only need to send the index of the words through the GPU data transfer bus, reducing data transfer overhead.

Word Embeddings (e.g. Word2Vec) in Go!

100+ Chinese Word Vectors 上百种预训练中文词向量

dna2vec: Consistent vector representations of variable-length k-mers

Word Embeddings for Information Retrieval

PyTorch implementation of Hash Embeddings (NIPS 2017). Submission to the NIPS Implementation Challenge.

cw2vec: Learning Chinese Word Embeddings with Stroke n-gram Information

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

Compact high quality word embeddings for Russian language

Using pre trained word embeddings (Fasttext, Word2Vec)

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

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

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

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.

Named-Entity Recognition in Persian Language

Sentiment Analysis: Deep Bi-LSTM+attention model

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

A Modern C++ Data Sciences Toolkit

all kinds of text classification models and more with deep learning

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

Named Entity Recognition using multilayered bidirectional LSTM

Implementation of triplet loss in TensorFlow

一个生产级、高性能、模块化、可扩展的中文NLP工具包。（中文分词、平均感知机、fastText、拼音、新词发现、分词纠错、BM25、人名识别、命名实体、自定义词典）

A collection of notebooks for Natural Language Processing from NLP Town

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

Curated List of Persian Natural Language Processing and Information Retrieval Tools and Resources

A python library for self-supervised learning on images.

All about Neural Networks!

Service Classification based on Service Description

🍊 🎑 Orange3 add-on for dealing with image related tasks

Nimfa: Nonnegative matrix factorization in Python

🔡 Token level embeddings from BERT model on mxnet and gluonnlp

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

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

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

Data augmentation for NLP, presented at EMNLP 2019

Keras, PyTorch, and NumPy Implementations of Deep Learning Architectures for NLP

Solves basic Russian NLP tasks, API for lower level Natasha projects

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

Programming Assignments and Lectures for Stanford's CS 224: Natural Language Processing with Deep Learning

An implementation of word2vec applied to [stanford philosophy encyclopedia](http://plato.stanford.edu/)