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splintered-reality
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39 Skills
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Build a production behavior-tree runtime (Blackboard, action/condition leaves, sequence/selector/parallel composites, decorators) and a Utility AI system (response curve…
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Orange Boosted is an accessible, ergonomic and Orange branded framework based on Bootstrap
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Compiler for LightGBM gradient-boosted trees, based on LLVM. Speeds up prediction by ≥10x.
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A Lightweight Decision Tree Framework supporting regular algorithms: ID3, C4.5, CART, CHAID and Regression Trees; some advanced techniques: Gradient Boosting, Random For…
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pure Go implementation of prediction part for GBRT (Gradient Boosting Regression Trees) models from popular frameworks
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A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of…
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A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python,…
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Ultra-fast matching engine written in Java based on LMAX Disruptor, Eclipse Collections, Real Logic Agrona, OpenHFT, LZ4 Java, and Adaptive Radix Trees.
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This skill should be used when scientists need help with research problem selection, project ideation, troubleshooting stuck projects, or strategic scientific decisions.…
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Golang configuration library using spf13/viper — layered precedence (flag > env > file > KV > default), BindPFlag/BindPFlags, SetEnvPrefix + SetEnvKeyReplacer + Automati…
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Build a weekly cadence of customer touchpoints using Opportunity Solution Trees, assumption mapping, and interview snapshots. Use when the user mentions "continuous disc…
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Build comprehensive attack trees to visualize threat paths. Use when mapping attack scenarios, identifying defense gaps, or communicating security risks to stakeholders.
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Rust implementation of behavior trees for deterministic AI (now with Python bindings)