Back to Home
🤖
Free
🤖Data & AI
✓ Verified

Testing toolkit using Pandas

World-class data science skill for statistical modeling, experimentation, causal inference, and advanced analytics. Expertise in Python (NumPy, Pandas, Scikit-learn), R, SQL, statistical methods, A/B testing, time series, and business intelligence. Includes experiment design, feature engineering, model evaluation, and stakeholder communication. Use when designing experiments, building predictive models, performing causal analysis, or driving data-driven decisions.

alirezarezvani

Core Features

Ready to Use

Quick integration into your workflow with minimal setup

Community Verified

Active open-source community with continuous updates

Completely Free

MIT/Apache licensed for commercial and personal use

Flexible Extension

Customizable and extendable based on your needs

How to Use

1Get Skill File

Download or copy the skill file from the source repository

Visit Source Repository

2Install to Claude

Place the skill file in Claude's skills directory (usually ~/.claude/skills/)。

3Start Using

Restart Claude or run the reload command to load the skill

Tip: Read the documentation and code carefully before first use to understand functionality and permission requirements

Technical Information

Author
alirezarezvani
Category
Data & AI
File Size
5.50 KB
Source Repository
alirezarezvani__claude-skills
Metadata
Includes YAML metadata
License
MIT
Download SkillView GitHub Source

All Skills from open-source community, preserving original authors' copyrights

alirezarezvani__claude-skills/engineering-team/senior-data-scientist/skill.md

Related Skills

Similar skills recommended based on tags and categories

Analysis toolkit for machine learning
🤖Data & AI
Claudeskillsfree

This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.

Author:K-Dense-AI
Analysis toolkit for machine learning (GO + ML)
🤖Data & AI
Claudeskillsfree

This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.

Author:K-Dense-AI
Analysis toolkit for machine learning (GO + ML) v2
🤖Data & AI
Claudeskillsfree

This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.

Author:K-Dense-AI
Claude Code agent generation system that creates custom a...
🎨Frontend
Claudeskillsfree

Claude Code agent generation system that creates custom agents and sub-agents with enhanced YAML frontmatter, tool access patterns, and MCP integration support following proven production patterns

Author:alirezarezvani