Milestones
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* Scale-out extraction - Distributed extraction and inference engine for Spark, HDFS/YARN, SLURM, Torque/GridEngine/PBS backends * Scale-out inference with numba * More user operations * Version control operations for incremental workflow * Database snapshot operations (PostgreSQL schema support) * Data programming support * More examples, documentation, and available tools - Co-reference - Entity-linking - Image/text fusion - CcT (CaffeConTroll) - ...
No due date* Out-of-core inference with user-guided sharding during grounding #592 * Proper categorical variable support with possible world key #545 * Data programming support (Supervision truthiness) #597 * Continuous feature values #562 #567 * CoreNLP wrapper (replacing Bazaar/Parser) #566 * Jupyter Notebook support #603 * Docker/Docker Compose support for build and production #564 #603 * TAB-separated JSONs format #565 * Scale-out extraction with Torque driver #513 * Compact `deepdive-plan` and `deepdive-do` output #603 * Automatic `deepdive-compile` #558 and many other usability improvements
Overdue by 10 year(s)•Due by November 9, 2016•105/105 issues closed