AI & ML Data Science Suite: Transform Raw Data to Models

Product Overview

The AI & ML Data Science Suite transforms raw data and questions into validated, documented models ready for production use. This skill facilitates comprehensive workflows including exploratory data analysis (EDA), feature engineering, model selection, evaluation, and seamless handoff to production environments.

What This Skill Does

• EDA Workflows: Enables structured data exploration with drift detection using tools like Pandas and Great Expectations.
• Feature Engineering: Constructs reproducible feature pipelines while preventing data leakage, ensuring train-serve parity.
• Model Selection: Provides strong tabular defaults and applies complexity incrementally as warranted.
• Evaluation and Reporting: Conducts slice analysis, assesses uncertainty, and generates model cards and production metrics.
• SQL Transformation: Utilizes SQLMesh for intermediate processes across staging and marts layers.
• MLOps: Supports continuous integration/deployment (CI/CD), continuous training (CT), and continuous monitoring (CM) practices.
• Production Patterns: Implements data contracts, ensures data lineage, and enables feedback loops and streaming features.

Who It Is For

This skill is designed for developers and data science teams using AI coding agents such as Claude Code, Cursor, and Codex, who require robust tools for data-driven modeling and operational integration.

Use Cases

• Data scientists conducting initial data profiling and quality checks.
• Engineers needing to establish and maintain feature parity between training and serving environments.
• Teams deploying models into production, requiring automated monitoring for drift detection and retraining triggers.
• Organizations aiming to document and evaluate models systematically for audit and improvement cycles.

Technical Details

• Tools: LightGBM, CatBoost, scikit-learn, PyTorch, Polars, lakeFS for data versioning.
• Data workflow emphasis on feature stores, automated retraining, and drift monitoring with Evidently.
• Integrates modern ML operations, supporting agentic ML loops consisting of plan, execute, evaluate, and improve steps.

Source & Licence

This package is built on open-source work published by joaoguirunas (joaoguirunas/team-os) and distributed under MIT. The original licence text and copyright notice are included in your download.

Personal and commercial use, modification and redistribution are permitted, provided the original copyright and licence notice are retained.

Your purchase covers curation, licence verification, packaging, documentation and instant delivery. It does not grant exclusive rights to the underlying open-source code, which remains available under its original licence.

Delivery & Support

• Delivery: instant — a secure download link is emailed to you as soon as payment is confirmed.
• Format: ZIP archive containing the skill files, documentation and the original licence.
• Support: support@mcpcart.com — we aim to reply within 2 business days.
• Updates: updates are included only where stated on this page.

Refunds

This is a digital product delivered immediately after purchase. By completing your order you request immediate delivery and acknowledge that, once the download has been accessed, the statutory right to cancel no longer applies to the extent permitted by law. Refund requests are handled in accordance with our published Refund Policy.

Claude, Codex, Gemini and Cursor are trademarks of their respective owners. MCP Cart is an independent marketplace and is not affiliated with, endorsed by, or sponsored by any of them. Compatibility references describe interoperability only.