CofactorCoFactor: Regularizing Matrix Factorization with Item Co-occurrence
Stars: ✭ 160 (-34.96%)
NimfaNimfa: Nonnegative matrix factorization in Python
Stars: ✭ 440 (+78.86%)
Hdc.caffeComplete Code for "Hard-Aware-Deeply-Cascaded-Embedding"
Stars: ✭ 98 (-60.16%)
Lmdb EmbeddingsFast word vectors with little memory usage in Python
Stars: ✭ 404 (+64.23%)
Nlp CubeNatural Language Processing Pipeline - Sentence Splitting, Tokenization, Lemmatization, Part-of-speech Tagging and Dependency Parsing
Stars: ✭ 353 (+43.5%)
Dict2vecDict2vec is a framework to learn word embeddings using lexical dictionaries.
Stars: ✭ 91 (-63.01%)
VectorhubVector Hub - Library for easy discovery, and consumption of State-of-the-art models to turn data into vectors. (text2vec, image2vec, video2vec, graph2vec, bert, inception, etc)
Stars: ✭ 317 (+28.86%)
Pytorch NlpBasic Utilities for PyTorch Natural Language Processing (NLP)
Stars: ✭ 1,996 (+711.38%)
Stock RnnPredict stock market prices using RNN model with multilayer LSTM cells + optional multi-stock embeddings.
Stars: ✭ 1,213 (+393.09%)
DecagonGraph convolutional neural network for multirelational link prediction
Stars: ✭ 268 (+8.94%)
KprnReasoning Over Knowledge Graph Paths for Recommendation
Stars: ✭ 220 (-10.57%)
HetuA high-performance distributed deep learning system targeting large-scale and automated distributed training.
Stars: ✭ 78 (-68.29%)
go2vecRead and use word2vec vectors in Go
Stars: ✭ 44 (-82.11%)
ElastiknnElasticsearch plugin for nearest neighbor search. Store vectors and run similarity search using exact and approximate algorithms.
Stars: ✭ 139 (-43.5%)
game2vecTensorFlow implementation of word2vec applied on https://www.kaggle.com/tamber/steam-video-games dataset, using both CBOW and Skip-gram.
Stars: ✭ 62 (-74.8%)
Graph 2d cnnCode and data for the paper 'Classifying Graphs as Images with Convolutional Neural Networks' (new title: 'Graph Classification with 2D Convolutional Neural Networks')
Stars: ✭ 67 (-72.76%)
Research2vecRepresenting research papers as vectors / latent representations.
Stars: ✭ 192 (-21.95%)
entity-embedPyTorch library for transforming entities like companies, products, etc. into vectors to support scalable Record Linkage / Entity Resolution using Approximate Nearest Neighbors.
Stars: ✭ 96 (-60.98%)
Deeplearning Nlp ModelsA small, interpretable codebase containing the re-implementation of a few "deep" NLP models in PyTorch. Colab notebooks to run with GPUs. Models: word2vec, CNNs, transformer, gpt.
Stars: ✭ 64 (-73.98%)
text2textText2Text: Cross-lingual natural language processing and generation toolkit
Stars: ✭ 188 (-23.58%)
Graph2gaussGaussian node embeddings. Implementation of "Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via Ranking".
Stars: ✭ 135 (-45.12%)
reachLoad embeddings and featurize your sentences.
Stars: ✭ 17 (-93.09%)
Ml Surveys📋 Survey papers summarizing advances in deep learning, NLP, CV, graphs, reinforcement learning, recommendations, graphs, etc.
Stars: ✭ 1,063 (+332.11%)
Cw2veccw2vec: Learning Chinese Word Embeddings with Stroke n-gram Information
Stars: ✭ 224 (-8.94%)
relation-networkTensorflow Implementation of Relation Networks for the bAbI QA Task, detailed in "A Simple Neural Network Module for Relational Reasoning," [https://arxiv.org/abs/1706.01427] by Santoro et. al.
Stars: ✭ 45 (-81.71%)
EmbeddingsvizVisualize word embeddings of a vocabulary in TensorBoard, including the neighbors
Stars: ✭ 40 (-83.74%)
Hash EmbeddingsPyTorch implementation of Hash Embeddings (NIPS 2017). Submission to the NIPS Implementation Challenge.
Stars: ✭ 126 (-48.78%)
Philo2vecAn implementation of word2vec applied to [stanford philosophy encyclopedia](http://plato.stanford.edu/)
Stars: ✭ 33 (-86.59%)
code-compassa contextual search engine for software packages built on import2vec embeddings (https://www.code-compass.com)
Stars: ✭ 33 (-86.59%)
Vec4irWord Embeddings for Information Retrieval
Stars: ✭ 188 (-23.58%)
KGE-LDAKnowledge Graph Embedding LDA. AAAI 2017
Stars: ✭ 35 (-85.77%)
Keras Textclassification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
Stars: ✭ 914 (+271.54%)
lda2vecMixing Dirichlet Topic Models and Word Embeddings to Make lda2vec from this paper https://arxiv.org/abs/1605.02019
Stars: ✭ 27 (-89.02%)
Dna2vecdna2vec: Consistent vector representations of variable-length k-mers
Stars: ✭ 117 (-52.44%)
Deep MihashCode for papers "Hashing with Mutual Information" (TPAMI 2019) and "Hashing with Binary Matrix Pursuit" (ECCV 2018)
Stars: ✭ 13 (-94.72%)
word2vec-tsneGoogle News and Leo Tolstoy: Visualizing Word2Vec Word Embeddings using t-SNE.
Stars: ✭ 59 (-76.02%)
CauseCode for the Recsys 2018 paper entitled Causal Embeddings for Recommandation.
Stars: ✭ 207 (-15.85%)
SentimentAnalysis(BOW, TF-IDF, Word2Vec, BERT) Word Embeddings + (SVM, Naive Bayes, Decision Tree, Random Forest) Base Classifiers + Pre-trained BERT on Tensorflow Hub + 1-D CNN and Bi-Directional LSTM on IMDB Movie Reviews Dataset
Stars: ✭ 40 (-83.74%)
entity-networkTensorflow implementation of "Tracking the World State with Recurrent Entity Networks" [https://arxiv.org/abs/1612.03969] by Henaff, Weston, Szlam, Bordes, and LeCun.
Stars: ✭ 58 (-76.42%)
Awesome Embedding ModelsA curated list of awesome embedding models tutorials, projects and communities.
Stars: ✭ 1,486 (+504.07%)
towheeTowhee is a framework that is dedicated to making neural data processing pipelines simple and fast.
Stars: ✭ 821 (+233.74%)
Eda nlpData augmentation for NLP, presented at EMNLP 2019
Stars: ✭ 902 (+266.67%)
JodieA PyTorch implementation of ACM SIGKDD 2019 paper "Predicting Dynamic Embedding Trajectory in Temporal Interaction Networks"
Stars: ✭ 172 (-30.08%)
Awesome 2vecCurated list of 2vec-type embedding models
Stars: ✭ 784 (+218.7%)
Catalyst🚀 Catalyst is a C# Natural Language Processing library built for speed. Inspired by spaCy's design, it brings pre-trained models, out-of-the box support for training word and document embeddings, and flexible entity recognition models.
Stars: ✭ 224 (-8.94%)
DeepehrChronic Disease Prediction Using Medical Notes
Stars: ✭ 220 (-10.57%)
SensegramMaking sense embedding out of word embeddings using graph-based word sense induction
Stars: ✭ 209 (-15.04%)
Cx db8a contextual, biasable, word-or-sentence-or-paragraph extractive summarizer powered by the latest in text embeddings (Bert, Universal Sentence Encoder, Flair)
Stars: ✭ 164 (-33.33%)
MagnitudeA fast, efficient universal vector embedding utility package.
Stars: ✭ 1,394 (+466.67%)
SpeedtorchLibrary for faster pinned CPU <-> GPU transfer in Pytorch
Stars: ✭ 615 (+150%)