Python address detector and parser

Table Detection and Extraction Using Deep Learning ( It is built in Python, using Luminoth, TensorFlow<2.0 and Sonnet.)

entity2rec generates item recommendation using property-specific knowledge graph embeddings

Factorization Machines for Recommendation and Ranking Problems with Implicit Feedback Data

A comprehensive and scalable set of string tokenizers and similarity measures in Python

⚙ 本项目为SWPU数据库原理及应用大作业《西柚外卖订餐系统》，基于Python+Flask+MySQL开发，轻量简洁

pyaddress is an address parsing library, taking the guesswork out of using addresses in your applications. We use it as part of our apartment search and apartment spider applications.

Pytorch implementation of Paper by Google Research - Representation Learning for Information Extraction from Form-like Documents.

Link Wikidata items to large catalogs

SigOpt wrappers for scikit-learn methods

geoparsepy is a Python geoparsing library that will extract and disambiguate locations from text. It uses a local OpenStreetMap database which allows very high and unlimited geoparsing throughput, …

Python Wrapper for the USPS API 🚚 📦

RdfPandas is a module providing RDF support for Pandas

Bloom Filter in Python using Murmurhash3

Pipeline for detecting fake news, covering data ingestion, doc embedding, classifier hypertuning & model ensembling. Quick walkthrough available in README. Execution logs on my FloydHub page.

Knowledge Embedding Based Graph Convolutional Network (WWW 2021)

An implementation of our paper in IJGIS 'A deep learning architecture for semantic address matching'

Entity resolution using zero labeled examples

The official client libraries for accessing SmartyStreets APIs from Python 2.7 and 3.5

Python implementation of TARQL

Create a cross-walk between zip code, county, and metropolitan area information.

This repository contains the code and data download links to reproduce the experiments of the PVLDB paper "Dual-Objective Fine-Tuning of BERT for Entity Matching" by Ralph Peeters and Christian Bizer.

In an effort to decrease the execution time of the OCR process, a multi-processing script was created using Python's multi-processing module.

Flask Webapp Using Machine Learning

Google Cloud Vision OCR return results per line

Addresser parses and normalizes street addresses and intersections. It's a port of `parse-address` and `Geo::StreetAddress::US`.

The project indents to extract horizontal lines and table present in the given image.