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。
Simplifies complex bioinformatics workflows in R using Bioconductor for RNA-seq, microarray, and single-cell genomic analysis.
Automates the creation, editing, and analysis of professional Excel spreadsheets with dynamic formulas and industry-standard formatting.
Integrates Fal.ai platform APIs to manage generative AI models, track resource usage, and monitor real-time pricing.
Designs and implements sophisticated LLM applications using the LangChain framework for agents, memory, and complex workflows.
Optimizes LLM context windows through strategic compaction, masking, and caching to improve model performance and reduce costs.
Provides expert guidance and implementation patterns for training large-scale Mixture-of-Experts (MoE) models using enterprise-grade Reinforcement Learning.
Provides expert guidance for implementing control theory routines, including LQR design, Kalman filtering, and system identification using the ctrlsys library.
Provides expert guidance and routine lookups for the ctrlsys control theory library, including LQR design, Riccati solvers, and system identification.
Enforces reproducible research and academic writing standards for Quarto and RMarkdown documents to eliminate generic AI-generated content.
Optimizes Rcpp and C++ extensions by enforcing memory safety, const-correctness, and high-performance vectorized patterns.
Enforces high-performance Julia conventions for scientific computing by eliminating type instability and inefficient coding patterns.
Enforces production-grade Python standards by eliminating generic AI coding patterns through PEP 8 compliance, rigorous type hinting, and pandas best practices.
Provides specialized machine learning algorithms for time series tasks including forecasting, classification, and anomaly detection using scikit-learn compatible APIs.
Scales Python workflows using parallel and distributed computing for datasets that exceed available memory.
Builds, fits, and validates sophisticated Bayesian models using PyMC's probabilistic programming interface.
Streamlines deep learning development by organizing PyTorch code into scalable, boilerplate-free Lightning modules and automated training workflows.
Performs exact symbolic mathematics in Python, including calculus, algebra, and complex equation solving.
Evaluates scholarly work using the ScholarEval framework to provide structured assessments, quantitative scoring, and actionable feedback across research dimensions.
Analyzes and visualizes complex network structures and graph data within Python environments.
Configures the development environment and installs essential dependencies for Planhaus catalog searching and data visualization.
Configures optimal LLM parameters and reasoning strategies based on evidence-backed research for specialized technical tasks.
Provides comprehensive documentation and implementation patterns for building AI-powered applications using the Vercel AI SDK.
Guides users through statistical test selection, assumption verification, and APA-formatted research reporting.
Simplifies working with pre-trained transformer models for NLP, computer vision, and audio tasks within Claude Code.
Analyzes real-time stock sentiment on X (Twitter) using Grok to provide actionable market insights and retail investor mood.
Automates scientific hypothesis generation and testing on tabular datasets by combining empirical data patterns with literature insights.
Generates professional, 50+ page market research reports in LaTeX format featuring advanced data visualizations and consulting-grade strategic frameworks.
Implements rigorous statistical modeling, econometrics, and time series analysis using Python's statsmodels library.
Enables real-time, AI-powered web searches with cited sources and advanced reasoning capabilities through the Perplexity model family.
Automates scientific data analysis and graphing workflows using GraphPad Prism scripting and XML manipulation.
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