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DeepLake is AI data infrastructure consisting of a multimodal data lake, a hybrid search engine, and a serverless vector database. It provides a PostgreSQL-based AI data runtime that combines multimodal storage with streaming pipelines to load and shuffle datasets from cloud storage directly into deep learning training pipelines. The system utilizes lazy indexing to store and slice images, audio, and video without loading entire files into memory. It enables retrieval-augmented generation by persisting high-dimensional embeddings in a serverless vector store and implementing hybrid search tha
Features from the rust language in javascript: Provides Traits/Type classes & a hashing infrastructure and an advanced library for working with sequences/iterators in js
Python library for creating data pipelines with chain functional programming
The main features of entilzha/pyfunctional are: Data Pipelines, Functional Utility Libraries.
Projects with overlapping indexed features include: a-synchronous/rubico — [A]synchronous Functional Programming. activeloopai/deeplake — DeepLake is AI data infrastructure consisting of a multimodal data lake, a hybrid search engine, and a serverless… adobe/ferrum — Features from the rust language in javascript: Provides Traits/Type classes & a hashing infrastructure and an advanced… akfamily/akshare — This project is a Python library designed for the programmatic retrieval and analysis of diverse financial datasets.… alanrsoares/prelude-js — functional/point-free utils for JavaScript. 1-liners/1-liners — Functional tools that couldn’t be simpler.
