Automatic normalization and data updates for data fetching libraries (react-query, vue-query, trpc, swr, rtk-query and more)
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Updated
Feb 16, 2026 - TypeScript
Automatic normalization and data updates for data fetching libraries (react-query, vue-query, trpc, swr, rtk-query and more)
[CVPR2021] Meta Batch-Instance Normalization for Generalizable Person Re-Identification
A flexible normalizer for user-generated content
Cross Modal Retrieval with Querybank Normalisation
Pipeline to analyse ChIP-Rx data, i.e ChIP-Seq with reference exogenous genome spike-in normalization
Python library for MIME type parsing, normalisation and grouping.
NAnostring quality Control dasHbOard.
An R package for the processing of plate reader and flow cytometry data. This includes: normalisation and calibration of plate reader data, and removing debris and doublets and calibration of flow cytometry data.
Designing and testing a relational database for The Happy Phone Company.
R/Bioconductor package - Peak Matrix Processing and signal batch correction for metabolomics data sets
R package for Variable Selection, Curve Fitting, Variable Conversion and Normalisation
PROFILE RNA-seq binarization technique.
Robust licence normalisation with a three-level hierarchy for common licences.
An automatic field transformation plugin for Mongoose 5. Any transformations are registered as save, update and findOneAndUpdate middleware.
This repository addresses a common challenge encountered within Digital Asset Management (DAM) systems: the ingestion of diverse audio file formats. This document outlines a robust methodology for normalising such assets into a unified and highly compatible .mp4 container.
This repository is totally focused on Feature Engineering Concepts in detail, I hope you'll find it helpful.
protGear is a package for protein microarray data processing just before the main analysis.
This project is a comprehensive proof-of-concept (PoC) for designing and implementing a data warehouse using a real-world Product Sales and Returns dataset. It demonstrates dimensional modeling, SQL-based ETL, data normalization, Tableau visualization, and a performance comparison between relational databases (SQL) and graph databases (Neo4j).
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