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Data Pipeline Architecture

data-engineering-data-pipeline

sickn33/antigravity-awesome-skills

You are a data pipeline architecture expert specializing in scalable, reliable, and cost-effective data pipelines for batch and streaming data processing.

Retail Demand Planning

inventory-demand-planning

sickn33/antigravity-awesome-skills

Guides multi-location retailers through demand forecasting, safety stock calculation, replenishment planning, promotional lift estimation, and ABC/XYZ segmentation, blending statistical best practices with ML-ready feature engineering to balance service levels and inventory costs.

Scalable Regulatory Network Inference

K-Dense-AI/claude-scientific-skills

Infers gene regulatory networks from bulk or single-cell expression data via GRNBoost2/GENIE3 with distributed computing support, ideal for transcriptomics workflows seeking TF-target relationships at scale.

GeoPandas Spatial Toolkit

K-Dense-AI/claude-scientific-skills

GeoPandas extends pandas with spatial vector data handling, letting teams read/write shapefiles, GeoJSON, GeoPackage and PostGIS, run reprojections, joins, overlays, buffering, and mapping alongside matplotlib/folium/Cartopy.

PyMC Bayesian Modeling

pymc-bayesian-modeling

K-Dense-AI/claude-scientific-skills

Structured workflow for building hierarchical Bayesian models with PyMC 5+, covering data prep, NUTS sampling, diagnostics, posterior checks, and predictive inference.

Guided Statistical Analysis

statistical-analysis

K-Dense-AI/claude-scientific-skills

Guides hypothesis testing, regression, correlation, and Bayesian analyses with automated assumption checks, diagnostics, power planning, and APA-style reporting so researchers can choose proper tests, interpret effect sizes, and document academic findings.

Statsmodels Statistical Modeling

K-Dense-AI/claude-scientific-skills

Statsmodels is a Python library for detailed regression and time-series models, giving econometrics-grade inference, diagnostics, residual analysis, model comparison, and forecasting tools when you need publication-ready tables and rigorous testing.

PyMC Bayesian Workflow

K-Dense-AI/claude-scientific-skills

Guides building, fitting, and validating Bayesian models with PyMC 5+, covering hierarchical structures, MCMC (NUTS), variational inference, diagnostic checks, model comparison (LOO/WAIC), and prediction steps for principled uncertainty quantification.

Product Analytics Playbook

analytics-product

sickn33/antigravity-awesome-skills

Guides product teams through PostHog and Mixpanel instrumentation, event funnels, retention cohorts, OKRs and north star dashboards to turn usage data into actionable decisions.

SwanLab Experiment Tracking

experiment-tracking-swanlab

Orchestra-Research/AI-Research-SKILLs

Guides ML teams through using SwanLab for tracking experiments, logging metrics and media, comparing runs, and running dashboards locally or self-hosted for robust workflow visibility.

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