Search Results for "share files"

Markdownify MCP is a Model Context Protocol server that converts many types of files and web content into clean Markdown. It supports formats such as PDFs, images, audio with transcription, DOCX, XLSX, and PPTX, along with web sources like YouTube transcripts, Bing results, and general webpages. Markdownify MCP is designed to simplify content extraction and make data easier to read, share, and reuse in structured workflows.

DVC (Data Version Control) is an open source tool designed to bring version control principles to machine learning and data science workflows. It enables developers and data scientists to track datasets, machine learning models, and experiment results in a way that integrates with existing Git repositories. Instead of storing large datasets directly in Git, DVC keeps lightweight metadata in the repository while storing the actual data in external storage systems. This approach allows teams...

...Additionally, Claude-Cognitive includes a pool coordinator to share state across multiple Claude Code instances, preserving what’s been learned or completed and preventing repetitive debugging or redundant exploration.

...Lingvo includes reference models and configurations for domains like machine translation, automatic speech recognition, language modeling, image understanding, and 3D object detection. Centralized hyperparameter configuration files allow researchers to share exact experiment setups so others can retrain and compare results reliably.

With the growing need to exchange information and share resources, information security has become more important than ever in both the public and private sectors. Although many technologies have been developed to control access to files or resources, to enforce security policies, and to audit network usages, there does not exist a technology that can verify that the user who is using the system is the same person who logged in.

Febrl (Freely Extensible Biomedical Record Linkage) does data standardisation (segmentation and cleaning) and probabilistic record linkage ("fuzzy" matching) of one or more files or data sources which do not share a unique record key or identifier.