Skill UI

Generates Python code and workflows for collaborative, content-based, or hybrid recommendation models, handling data prep, training, evaluation, and scalability so Claude can deliver tailored suggestions across domains.

A comprehensive, end-to-end workflow for building product features guided by rigorous data insights. This skill guides users through the entire lifecycle, encompassing exploratory data analysis, forming measurable business hypotheses, designing statistical A/B tests, architecting data pipelines, and implementing robust backend/frontend instrumentation. It ensures that every feature iteration is validated by data and measured for impact.

This skill models the expertise of a senior data scientist, covering the entire data science lifecycle. It provides advanced capabilities in statistical modeling, machine learning (deep learning, XGBoost), predictive analytics, and business intelligence. From raw data exploration (EDA) to deploying production-ready models and creating actionable dashboards, it covers technical depth across Python, R, SQL, and cloud platforms, while applying domain knowledge in finance, marketing, and operations.

This guide outlines a production-ready lakehouse architecture using Unity Catalog, Delta Lake, and the Medallion pattern. It provides best practices for organizing Databricks workspaces, implementing three-level governance, defining compute strategies, and adopting CI/CD best practices with Asset Bundles for robust team collaboration.

A comprehensive guide to implementing best practices for security within Databricks. Learn how to manage secrets using scoped storage, enforce the principle of least privilege via Unity Catalog grants, audit API tokens, and apply advanced data protection techniques like column-level masking and row-level security for enhanced data governance and compliance.

NeMo Curator streams GPU-accelerated curation for LLM training, with super-fast fuzzy deduplication, multimodal quality filters, semantic dedupl, PII redaction, NSFW checks, and RAPIDS-scaled pipelines for prepping massive corpora.

Aeon is a scikit-learn compatible toolkit for time series machine learning, covering classification, regression, clustering, forecasting, anomaly detection, segmentation, similarity search, and feature extraction on temporal data.

BioServices provides Python wrappers for 40+ bioinformatics services, allowing cross-database queries, identifier mapping, pathway exploration, and sequence or compound research within consistent workflows.

Automates detection and deep exploratory analysis across 200+ scientific data formats, assessing quality, extracting metadata, and recommending visualizations while generating markdown reports that guide downstream workflows and highlight structure and distributions.

Plotly is a Python graphing library for interactive, publication-quality visuals that bring hover, zoom, animation, and dashboard-ready exports to exploratory analysis and presentations.

QuTiP is a Python toolbox for simulating open and closed quantum systems, offering solvers for master equations, trajectory methods, visualization, and analysis tailored to quantum research, education, and exploratory physics studies.

Seaborn is a powerful Python library for creating publication-quality statistical graphics. It is designed for dataset-oriented plotting, making it ideal for exploratory data analysis, multivariate analysis, and visualizing complex relationships, distributions, and comparisons with minimal code. It builds upon Matplotlib, offering high-level interfaces for functions like scatterplots, heatmaps, and pair plots.