WarpDrive is a lightweight data library for web apps — universal, typed, reactive, and ready to scale.
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Updated
Dec 24, 2024 - TypeScript
WarpDrive is a lightweight data library for web apps — universal, typed, reactive, and ready to scale.
data load tool (dlt) is an open source Python library that makes data loading easy 🛠️
TypeScript/JavaScript client library for Convex
Podium: a framework agnostic Python NLP library for data loading and preprocessing
Lightweight data loading and caching library for android
Local-first federated analytics query engine using DuckDB.
Contains all my data science projects.
High-level API for tar-based dataset
This repository is a working ETL framework which utilizes user data from Spotify API using ➲Python for Extraction and Transformation ➲SQL for Data Loading and Staging ➲Airflow for Data Orchestration and Monitoring ➲PowerBI for Reporting
A fast and easy-to-use Remote sensing Image format COnverter for High-throughput Deep-Learning (rico-hdl).
Data loading with combined async Rust stream and Python
An Android library for data load with cache and loading state
Syracuse University, Masters of Applied Data Science - IST 722 Data Warehouse
Get the DeepLesion CT Image data set into a GCP Storage Bucket
React software architecture techniques and examples. Includes server-side rendering, data loading and code splitting.
A slick loader to use during your AJAX calls or data processing
This tool rapidly converts loose files scattered within any folder into a consolidated H5 file. This allows for faster read operations with lower memory requirement.
ColumnCore is a high-performance analytical database system designed for beginners or small projects. It supports a rich SQL dialect, runs within the same process as the application, has a vectorized query execution engine, and uses a columnar storage format.
challenges : (React Router data loading, Redux, Redux Toolkit, thunks, Tailwind CSS)
`Spltr` is a simple PyTorch-based data loader and splitter. It may be used to load arrays and matrices or Pandas DataFrames and CSV files containing numerical data with subsequent split it into train, test (validation) subsets in the form of PyTorch DataLoader objects.
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