sam-splat

ant-design

An enterprise-class UI design language and React UI library

desktop

Focus on what matters instead of fighting with Git.

gridstudio

Grid studio is a web-based application for data science with full integration of open source data science frameworks and languages.

pke

Python Keyphrase Extraction module

digimend-kernel-drivers

DIGImend graphics tablet drivers for the Linux kernel

K-BERT

Source code of K-BERT (AAAI2020)

bitarray

efficient arrays of booleans for Python

pytorch-slimming

Learning Efficient Convolutional Networks through Network Slimming, In ICCV 2017.

slimming

Learning Efficient Convolutional Networks through Network Slimming, In ICCV 2017.

spot

Spot is a concise, developer-friendly way to describe your API contract.

rick-and-morty-info

Made with Clean architecture + TDD + GraphQL + flutter_bloc + CodeCov + GitHooks + GitHub Actions (CI/CD) and finally with 💙

ai-research-keyphrase-extraction

EmbedRank: Unsupervised Keyphrase Extraction using Sentence Embeddings (official implementation)

CollisionDetection

A book and examples on collision detection

neural_sequence_labeling

A TensorFlow implementation of Neural Sequence Labeling model, which is able to tackle sequence labeling tasks such as POS Tagging, Chunking, NER, Punctuation Restoration and etc.

OpenKP

Automatically extracting keyphrases that are salient to the document meanings is an essential step to semantic document understanding. An effective keyphrase extraction (KPE) system can benefit a wide range of natural language processing and information retrieval tasks. Recent neural methods formulate the task as a document-to-keyphrase sequence-to-sequence task. These seq2seq learning models have shown promising results compared to previous KPE systems The recent progress in neural KPE is mostly observed in documents originating from the scientific domain. In real-world scenarios, most potential applications of KPE deal with diverse documents originating from sparse sources. These documents are unlikely to include the structure, prose and be as well written as scientific papers. They often include a much diverse document structure and reside in various domains whose contents target much wider audiences than scientists. To encourage the research community to develop a powerful neural model with key phrase extraction on open domains we have created OpenKP: a dataset of over 150,000 documents with the most relevant keyphrases generated by expert annotation.

ake-datasets

Large, curated set of benchmark datasets for evaluating automatic keyphrase extraction algorithms.

go-restful-openapi

OpenAPI extension in Go for the go-restful package

LuaToTypeScript

Converts Lua code to TypeScript

xnotify

Cross platform file notification with built-in task execution and a client/server feature to overcome virtual folders without relying on polling.

Morph.py

A neural architecture optimizer, targeted at model-size w.r.t. accuracy

key2vec

pointer-networks-pytorch

Pointer Networks in PyTorch

licenser

tool to put a copyright notice header in source files

semeval-2010-pre

Preprocessed SemEval-2010 benchmark dataset for keyphrase extraction

sashay

Generate OpenAPI 3.0 (Swagger) files from real, working Go code.

xconnect

exploring network connectivity in a microservice landscape

Instance-Segmentation-based-Semantic-Matting-for-Compositing-Applications

Publication and Poster

tokenman

small Go library for JWT token management

dollar

The $1 Unistroke Recognizer (Go version)

neural_sequence_labeling

A TensorFlow implementation of Neural Sequence Labeling model, which is able to tackle Part-of-Speech (POS) Tagging, Chunking and Named Entity Recognition (NER) tasks.