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Results for “probabilistic-programming”

3 skills
k-dense-ai
pymc
Build, fit, validate, and compare Bayesian models using PyMC's modern API, including hierarchical models, MCMC sampling, variational inference, posterior predictive checks, and model comparison.
30.2k · bundle
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k-dense-ai
pacsomatic
Validates inputs, generates samplesheets and launch scripts, and optionally executes nf-core/pacsomatic matched tumor-normal workflows from BAM files, supporting local runs and scheduler submission (LSF/Slurm/PBS/SGE).
30.2k · bundle
michaelschecht
odds-modeling
Build predictive models for sports and event outcomes using statistical methods, ELO ratings, regression, Monte Carlo simulation, and machine learning. Use when creating power rankings, projecting game outcomes, estimating win probabilities, or building a quantitative edge. Also trigger for 'prediction model', 'ELO rating', 'power rankings', 'win probability', 'Monte Carlo', 'regression model', 'expected goals', or 'predictive analytics'.
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