Enables agents to migrate and synchronize data into SurrealDB from MongoDB, PostgreSQL, MySQL, Neo4j, Kafka, and JSONL, including full imports and incremental CDC synchronization.
Data migration and synchronization to SurrealDB from MongoDB, PostgreSQL, MySQL, Neo4j, Kafka, and JSONL. Full and incremental CDC sync. Part of the surreal-skills collection.
Provides sklearn-style estimators for incrementally updating covariance, correlation, precision, and location matrices from streaming observations using constant work per observat…
Enables Python agents to update, assess, compare, and select online covariance, correlation, and precision estimators for streaming or dynamic-universe data.
Wraps positional online covariance estimators to process keyed observations whose named series can remain fixed or change dynamically over time.
Recommends covariance estimator classes for a 2-D dataset using dimension, conditioning, rank, correlation, and tail-behavior features, and exposes those features for inspection.
Guides an AI agent through end-to-end Kaggle competitions, including validation, modeling, OOF predictions, ensembling, remote notebook pipelines, artifact handoffs, submission sc…
Analyzes e-commerce reviews using 22-dimension AI tagging to extract customer profiles, pain points, VOC, product opportunities, anomaly signals, reports, dashboards, and optional…
Queries Open Library's public catalog for books, authors, works, editions, ISBNs, ratings, and cover URLs through a keyless Python CLI.
Assesses, designs, and evolves data architectures through workload analysis, platform and modeling tradeoffs, governance, data products, data mesh, event-driven flows, and migrati…
