east-py-datascience
Data science and machine learning platform functions for the East language (TypeScript types). Use when writing East programs that need optimization (MADS, Optuna, SimAnneal, Scipy), machine learning (XGBoost, LightGBM, NGBoost, Torch MLP, Lightning, GP), ML utilities (Sklearn preprocessing, metrics, splits), conformal prediction (MAPIE), or model explainability (SHAP). Triggers for: (1) Writing East programs with @elaraai/east-py-datascience, (2) Derivative-free optimization with MADS, (3) Bayesian optimization with Optuna, (4) Discrete/combinatorial optimization with SimAnneal, (5) Gradient
npx skills add majiayu000/claude-skill-registry --skill east-py-datascience --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# East Data Science Data science and machine learning platform functions for the East language. Provides optimization, ML models, preprocessing, and explainability. ## Quick Start ```typescript import { East, FloatType, variant } from "@elaraai/east"; import { MADS } from "@elaraai/east-py-datascience"; // Define objective function const objective = East.function([MADS.Types.VectorType], FloatType, ($, x) => { const x0 = $.let(x.get(0n)); const x1 = $.let(x.get(1n)); return $.return(x0.multiply(x0).add(x1.multiply(x1))); }); // Optimize const optimize = East.function([], MADS.Types.ResultType, $ => { const x0 = $.let([0.5, 0.5]); const bounds = $.let({ lower: [-1.0, -1.0], upper: [1.0, 1.0] }); const config = $.let({ max_bb_eval: variant('some', 100n), display_degree: variant('some', 0n), direction_type: variant('none', null), initial_mesh_size: variant('none', null), min_mesh_size: variant('none', null), seed: variant('some', 42n), }); return $.return(MADS.optimize(objective, x0, bounds, variant('none', null), config)); }); ``` ## Decision Tree: Which Module to Use ``` Task → What do you need? │ ├─ MADS (derivative-free continuous optimization) │ └─ .optimize() │ ├─ Optuna (Bayesi
- Quick Start
- Decision Tree: Which Module to Use
- Common Types
- Reference Documentation
- Available Modules
- Accessing Types
- Common Patterns
- Train and Predict
- Optimization
What does the east-py-datascience skill do?
Data science and machine learning platform functions for the East language (TypeScript types). Use when writing East programs that need optimization (MADS, Optuna, SimAnneal, Scipy), machine learning (XGBoost, LightGBM, NGBoost, Torch MLP, Lightning, GP), ML utilities (Sklearn preprocessing, metrics, splits), conformal prediction (MAPIE), or model explainability (SHAP). Triggers for: (1) Writing East programs with @elaraai/east-py-datascience, (2) Derivative-free optimization with MADS, (3) Bayesian optimization with Optuna, (4) Discrete/combinatorial optimization with SimAnneal, (5) Gradient
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill east-py-datascience --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.