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netl-automatic-topic-labelling-

Generating labels for topics automatically using neural embeddings

neural-summary-tensorflow

TensorFlow implementation of "A Neural Attention Model for Abstractive Summarization"

neuraltalk

NeuralTalk is a Python+numpy project for learning Multimodal Recurrent Neural Networks that describe images with sentences.

nlpcaffe

nlpir

nlpnet

A neural network architecture for NLP tasks, inspired in the SENNA system. It uses as input vectors built through Vector Space Models and avoid external NLP tools. Currently, it can perform POS tagging and SRL.

nous

NOUS Knowledge Graph

nre

Neural Relation Extraction, including CNN, PCNN, CNN+ATT, PCNN+ATT

nrlpapers

Must-read papers on network representation learning (NRL)/network embedding (NE)

oiwe

Online Interpretable Word Embeddings

onlinehdp

C++ implementation for online variational inference for hierarchical dirichlet process

opendl

屹立深度之巅

openke

An Open-Source Package for Knowledge Embedding (KE)

opennre

An Open-Source Package for Neural Relation Extraction (NRE)

optimus

Train, evaluate and deploy Convolutional Neural Network based text classifiers

oracle2neo4j

Load huge data set from Oracle to Neo4j.

owl2-swrl-tutorial

sources for my OWL2 and SWRL tutorial

owlapi

OWL API main repository

p3c

Alibaba Java Coding Guidelines pmd implements and IDE plugin

paddle

PArallel Distributed Deep LEarning

pai

Resource scheduling and cluster management for AI

paracel

Distributed training framework with parameter server

paragraph2vec

passage

A little library for text analysis with RNNs.

phd-thesis

Repository of my thesis "Understanding Random Forests"

plato

腾讯高性能图计算框架Plato

pmtk3

Probabilistic Modeling Toolkit for Matlab/Octave.

pocketflow

An Automatic Model Compression (AutoMC) framework for developing smaller and faster AI applications.

predict-customer-churn

A general-purpose framework for solving problems with machine learning applied to predicting customer churn

predicting_ctr

Predicting Click-Through Rate for New Users and Advertisers