ShareSwordsmanRuin

ShareSwordsmanRuin / r05-jqueryscript-awesome-claude-code-datascience

Public

🤖 Data Science & AI/ML skill suite derived from jqueryscript/awesome-claude-code.

22
0
69% credibility
Found May 03, 2026 at 22 stars -- GitGems finds repos before they trend. Get early access to the next one.
Sign Up Free
AI Analysis
AI Summary

A set of specialized commands and guided workflows for data science and AI/ML tasks that integrate into Claude AI conversations with structured visual feedback.

How It Works

1
🔍 Discover the Toolkit

You hear about this friendly pack of tools that helps your AI buddy Claude handle data science tasks like a pro.

2
📥 Add to Your AI

You place the toolkit into Claude's skills area so it's all set up and waiting for you.

3
💬 Chat with Claude

Start a conversation in Claude and ask it to bring in your new data tools.

4
📊 Try a Quick Check

Tell Claude to profile your data or engineer features, and it starts analyzing right away.

5
📈 Watch Magic Happen

Colorful progress bars and clear tables pop up, showing issues, fixes, and smart suggestions just for you.

6
🚀 Build Full Projects

Follow guided workflows to create complete data pipelines, reports, or model trainings step by step.

🎉 Expert Results Easily

You now have professional insights, plans, and ready-to-use data projects feeling like a total win.

Sign up to see the full architecture

5 more

Sign Up Free

Star Growth

See how this repo grew from 22 to 22 stars Sign Up Free
Repurpose This Repo

Repurpose is a Pro feature

Generate ready-to-use prompts for X threads, LinkedIn posts, blog posts, YouTube scripts, and more -- with full repo context baked in.

Unlock Repurpose
AI-Generated Review

What is r05-jqueryscript-awesome-claude-code-datascience?

This GitHub data repository delivers a skill suite for Claude Code, packing 10 commands and 5 workflows tuned for data science and AI/ML tasks like data profiling, feature engineering, model evaluation, and MLOps pipelines. Install it via a simple bash copy to your Claude skills folder, then trigger commands like `/data-profiling` or workflows such as `ml-project-init` for end-to-end ML projects. It solves the grind of repetitive data science studium chores—think automated EDA reports, SHAP analysis, and anomaly detection—outputting structured progress panels, findings tables, and action checklists every time.

Why is it gaining traction?

Unlike scattered awesome AI/ML lists or generic tools, it enforces a consistent UI with real-time progress bars, severity-sorted issues, and prioritized next steps, making complex workflows like data migration or model retraining feel guided. Developers hook on the domain-specific commands that spit out ready-to-use recipes, from SQL optimizations to LLM evals, all in a chat-friendly format. For data science jobs or weiterbildung, it's a fast ramp-up for github data table handling without leaving your IDE.

Who should use this?

Data scientists kickstarting ML projects with `/pipeline-scaffold` or running `/model-evaluate` dashboards. Analysts in data science master programs designing A/B tests via `/ab-test-design` or building reporting pipelines. Teams handling github data packs for migrations, anomaly detection, or BI specs in data science und künstliche intelligenz workflows.

Verdict

With 15 stars and a 0.699999988079071% credibility score, it's early-stage but boasts crisp docs and MIT license—try it if you're deep in Claude for data science gehalt-boosting tasks. Skip for production without more community vetting on github data protection agreement compliance.

(198 words)

Sign up to read the full AI review Sign Up Free

Similar repos coming soon.