How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.
Algorithm is a library of tools that is used to create intelligent applications.
The main features of cosmicmind/algorithm are: Data Management, Data Structures.
Projects with overlapping indexed features include: attaswift/btree — Fast sorted collections for Swift using in-memory B-trees. activeloopai/hub — Hub is a multimodal AI data lake and vector database designed for storing and querying embeddings, text, audio, and… addresscloud/aws-lambda-docker-rasterio — AWS Lambda Container Image with Python Rasterio for querying Cloud Optimised GeoTiffs. ahmed-ali/jsonexport — JSONExport is a multi-language code generator and JSON schema converter that transforms JSON data structures into… aio-libs/janus — Thread-safe asyncio-aware queue for Python. activeloopai/deeplake — DeepLake is AI data infrastructure consisting of a multimodal data lake, a hybrid search engine, and a serverless…
Fast sorted collections for Swift using in-memory B-trees
Hub is a multimodal AI data lake and vector database designed for storing and querying embeddings, text, audio, and images. It functions as a dataset version control system and a machine learning data streaming engine to support large-scale model training. The system utilizes a serverless PostgreSQL vector store to index high-dimensional embeddings for semantic search. It provides a visual interface for inspecting multimodal datasets and viewing annotations such as bounding boxes and masks. The platform handles cloud-agnostic storage synchronization and implements lazy, compressed data strea
AWS Lambda Container Image with Python Rasterio for querying Cloud Optimised GeoTiffs.
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