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Advanced Data Pipeline Engineering Guide

senior-data-engineer

alirezarezvani/claude-skills

This comprehensive guide details the expertise needed for a Senior Data Engineer. It covers building, optimizing, and governing scalable data pipelines and robust ETL/ELT systems using modern tools like Spark, Kafka, Airflow, and dbt. Includes decision frameworks for architecting data solutions (Batch vs Streaming, Lakehouse vs Warehouse) and implementing advanced data modeling patterns.

Senior Data Scientist Skill

senior-data-scientist

alirezarezvani/claude-skills

Guides senior data scientists through designing controlled experiments, engineering structured features, training ML models, and translating results into decisions using Python, R, SQL, and tools like Scikit-learn, XGBoost, and MLflow.

Sequelize Model Creator

sequelize-model-creator

jeremylongshore/claude-code-plugins-plus-skills

Automates Sequelize model creation for backend development, offering step-by-step guidance, best practices, and production-ready code/config validation when working with Node.js, Python, Go, databases, caching, messaging, and microservices.

Simple Preference Optimization for LLM Alignment

Orchestra-Research/AI-Research-SKILLs

SimPO (Simple Preference Optimization) is a state-of-the-art, reference-free method designed for aligning Large Language Models (LLMs) using human preference data. It is an efficient alternative to DPO and PPO, notably outperforming DPO without requiring a separate reference model. It is ideal for practitioners who need faster, simpler, and more resource-efficient fine-tuning for preference alignment.

Sklearn Pipeline Builder

sklearn-pipeline-builder

jeremylongshore/claude-code-plugins-plus-skills

Automates sklearn pipeline builder tasks within ML training, activating on relevant triggers to guide data prep, model training, hyperparameter tuning, and experiment tracking with production-ready code and standards validation.

Dataset Splitter Tool

splitting-datasets

jeremylongshore/claude-code-plugins-plus-skills

Automates splitting datasets into training, validation, and test subsets by generating and running Python code so you can quickly prepare data for machine learning model training and evaluation.

Swift Actor For Thread-Safe Persistence

swift-actor-persistence

affaan-m/everything-claude-code

This pattern demonstrates how to build a robust, thread-safe data persistence layer in Swift using the 'actor' model. It combines fast in-memory caching with reliable file-backed storage, automatically eliminating data races and the need for manual locks. Ideal for offline-first applications and managing shared mutable state in modern Swift concurrency.

Swift 6.2 Structured Concurrency Patterns

swift-concurrency-6-2

affaan-m/everything-claude-code

A guide to the Swift 6.2 concurrency model, which mandates default single-threaded execution to eliminate accidental data races. Learn how to use MainActor for isolated consistency and utilize the @concurrent attribute for explicitly offloading CPU-intensive tasks to background threads, ensuring safe and predictable application architecture.

Tensorflow Model Trainer

tensorflow-model-trainer

jeremylongshore/claude-code-plugins-plus-skills

Auto-activating skill that guides tensorflow model trainer workflows, covering data preparation, model training, hyperparameter tuning, and experiment tracking with production-ready code and standards validation.

Machine Learning Training

training-machine-learning-models

jeremylongshore/claude-code-plugins-plus-skills

Automates the end-to-end training of machine learning models by analyzing datasets, selecting suitable algorithms, tuning parameters, performing cross-validated training, and emitting performance metrics plus a saved model artifact.

AI Ethics Fairness Audit

validating-ai-ethics-and-fairness

jeremylongshore/claude-code-plugins-plus-skills

Assesses AI/ML models and datasets for ethical risks, fairness concerns, and bias, generating reports and mitigation guidance via the ai-ethics-validator plugin whenever a user requests an ethics review or bias detection.

Secure Data Management For ML Training

vastai-data-handling

jeremylongshore/claude-code-plugins-plus-skills

A comprehensive guide to managing training data and model artifacts securely on cloud GPU instances (e.g., Vast.ai). It covers best practices for data transfer (SCP, compressed, cloud staging), implementing AES-256 encryption, managing checkpoints to S3, and performing secure cleanup before instance destruction, ensuring compliance and data integrity.

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