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Search Feature Engineering , found 9 results

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Codebase Refactor Cleanup

codebase-cleanup-refactor-clean

sickn33/antigravity-awesome-skills

Analyzes messy codebases and applies SOLID, clean-code, and modern engineering practices to improve readability, stability, and maintainability before new feature work.

Data-Driven Feature Development

data-engineering-data-driven-feature

sickn33/antigravity-awesome-skills

Build features guided by data insights, A/B testing, and continuous measurement using specialized agents for analysis, implementation, and experimentation.

Databricks MLflow Workflow

databricks-core-workflow-b

jeremylongshore/claude-code-plugins-plus-skills

Guides ML engineers through the Databricks secondary workflow that links Feature Store engineering, MLflow experiment tracking, model registry versioning, and serving so production-grade models can be trained and deployed.

Feature Engineering Toolkit

engineering-features-for-machine-learning

jeremylongshore/claude-code-plugins-plus-skills

Feature Engineering Toolkit automates creating, selecting, and transforming dataset features to improve machine learning models; use it whenever you need new interactions, automatic selection, scaling, or encoding to boost accuracy and interpretability.

Feature Engineering Helper

feature-engineering-helper

jeremylongshore/claude-code-plugins-plus-skills

Automatically activates when you mention feature engineering helper, offering guidance on data preparation, model training, hyperparameter tuning, and experiment tracking for ML projects.

Production ML Engineering Playbook

sickn33/antigravity-awesome-skills

Guides ML engineers in building production-ready systems with PyTorch 2.x, TensorFlow, and modern tooling, covering serving pipelines, feature engineering, monitoring, and MLOps infrastructure for scalable, reliable deployments.

Sales Engineer Playbook

alirezarezvani/claude-skills

Centralizes RFP/RFI analysis, competitor feature comparisons, and POC/demo planning for pre-sales engineering, guiding discovery through closing phases with scripted automation (RFP analyzer, competitive matrix, POC planner).

Aeon Time Series Toolkit

K-Dense-AI/claude-scientific-skills

Aeon is a scikit-learn compatible toolkit for classification, regression, clustering, forecasting, anomaly detection, segmentation, similarity search, and feature engineering on temporal data.

UMAP Manifold Reduction

K-Dense-AI/claude-scientific-skills

UMAP-Learn delivers fast nonlinear dimensionality reduction for visualization, clustering prep, and feature engineering; it mirrors scikit-learn APIs and supports supervised/semi-supervised embeddings with tunable parameters.

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