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.
Library for exploring and validating machine learning data
The main features of tensorflow/data-validation are: Data Visualization, Data Validation, Data Validation and Anomaly Detection, Developer Tools.
Projects with overlapping indexed features include: seldonio/alibi-detect — Algorithms for outlier, adversarial and drift detection. pydantic/pydantic — Pydantic is a data validation and serialization library that enforces schema constraints and performs type conversion… nytimes/covid-19-data — This project is a public health dataset providing historical and real-time COVID-19 case and death counts across the… 0xax/erlang-bookmarks — All about erlang programming language [powerd by community]. 30-seconds/30-seconds-of-code — This project is a developer knowledge base and a curated library of programming code snippets. It serves as a… 21st-dev/magic-mcp — Magic MCP is a Model Context Protocol server and AI component generator that translates natural language descriptions…
Pydantic is a data validation and serialization library that enforces schema constraints and performs type conversion on complex data structures. It utilizes standard Python type annotations to define data models, allowing developers to establish structured schemas that automatically enforce business rules and constraints without the need for custom domain-specific languages. The library distinguishes itself by transforming high-level model definitions into optimized code during initialization to minimize runtime overhead. It supports recursive validation for nested data structures and employ
Algorithms for outlier, adversarial and drift detection
This project is a public health dataset providing historical and real-time COVID-19 case and death counts across the United States. It consists of a collection of CSV files containing time-series pandemic data organized by date, state, and county. The dataset includes specialized records for institutional outbreaks, tracking infection and death rates within correctional facilities, colleges, and universities. It also provides statistics on excess mortality to estimate total pandemic impact and survey-based data on mask usage prevalence across different counties. To facilitate geographic anal
All about erlang programming language powerd by community