发现data science & ml类别的 Claude 技能。浏览 61 个技能,找到适合您 AI 工作流程的完美功能。
Optimizes Python data processing using production-grade pandas patterns for large-scale DataFrame manipulation and memory efficiency.
Computes and analyzes complex investment performance metrics including TWR, MWR, CAGR, and annualized returns.
Analyzes and evaluates alternative investments including hedge funds, private equity, and venture capital using industry-standard metrics and frameworks.
Analyzes user retention and behavioral patterns over time to optimize customer lifecycle and lifetime value.
Generates standardized benchmark test cases for the CAC evaluation system across code, math, logic, and comprehensive categories.
Analyzes cryptocurrency fundamentals, DeFi protocols, and blockchain metrics to provide deep insights into the digital asset ecosystem.
Cleans and processes malformed or messy CSV files using automated detection of encodings, delimiters, and data types.
Streamlines machine learning experiment configuration using declarative decorators and automatic CLI generation.
Implements best practices for Hugging Face Transformers including model loading, fine-tuning, and inference optimization.
Builds sophisticated, reactive web applications and data dashboards using the HoloViz Panel and Param framework.
Master color management and accessible visual styling using perceptually uniform Colorcet palettes for scientific data visualizations.
Implements declarative, type-safe parameter systems with automatic validation and reactive UI generation for Python applications.
Enables natural language data exploration and conversational analytics through AI-powered agents and automated SQL generation.
Simplifies astronomical data analysis and processing using the Astropy ecosystem for coordinates, units, and FITS files.
Streamlines scientific Python development by managing complex conda and PyPI dependencies with fast, reproducible Pixi environments.
Analyzes and processes labeled multidimensional scientific datasets using Xarray, Dask, and geospatial extensions.
Creates complex, interactive, and multi-dimensional data visualizations using the HoloViz ecosystem.
Creates interactive, high-performance geographic visualizations and spatial data analyses using GeoViews and GeoPandas.
Reduces LLM inference costs by automatically routing requests to the most cost-effective and capable models across major providers.
Generates interactive, publication-quality visualizations and dashboards using the HoloViz ecosystem.
Standardizes the creation and distribution of Python packages using modern Hatchling and PEP 621 conventions for scientific computing.
Enables high-performance rasterization and visualization for massive datasets exceeding 100 million points using Datashader and HoloViews.
Standardizes data quality across ETL pipelines with custom validation patterns, schema evolution, and automated test assertions.
Orchestrates complex data pipelines and automated workflows using Apache Airflow's DAG-based architecture and extensive operator ecosystem.
Implements production-grade machine learning lifecycles using MLflow for experiment tracking, model registration, and multi-cloud deployment patterns.
Architects and optimizes scalable, distributed data pipelines and analytics systems using the Apache Spark framework.
Automates professional-grade spreadsheet creation, financial modeling, and data analysis with dynamic formula preservation and error-free validation.
Architects production-grade LLM applications using advanced LangChain orchestration patterns, agents, and complex memory systems.
Evaluates RAG system performance through automated metrics, LLM-as-judge scoring, and competitive benchmarking.
Recommends optimal document chunking strategies to improve retrieval quality and accuracy in RAG pipelines.
Scroll for more results...