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。
Assesses machine learning model performance using comprehensive metrics to facilitate validation, testing, and optimization workflows.
Provides a persistent cognitive architecture for AI agents to maintain long-term memory, context, and identity across multiple sessions.
Generates professional plots, charts, and graphs from raw data with intelligent, automatic visualization type selection.
Automates financial budget-vs-actual variance analysis with professional reporting, automated commentary, and executive summaries.
Builds sophisticated recommendation systems using collaborative filtering, content-based algorithms, and hybrid machine learning models.
Processes and analyzes massive tabular datasets exceeding RAM limits using high-performance out-of-core DataFrames.
Enables programmatic access and analysis of the CZ CELLxGENE Census, a collection of over 61 million standardized single-cell genomics records.
Performs rigorous statistical modeling and econometric analysis using Python's statsmodels library for deep data insights.
Analyzes, visualizes, and manipulates complex network structures and graph data using the NetworkX Python library.
Provides deep interpretability and explainability for machine learning models using advanced techniques like SHAP and LIME.
Automates laboratory workflows and controls liquid handling robots and analytical equipment through a hardware-agnostic Python interface.
Integrates Codex CLI command patterns into Claude Code to enable advanced multi-agent planning and high-reasoning execution.
Automates budget vs. actual financial variance analysis with professional reporting, materiality flagging, and executive summaries.
Tracks and manages AI/ML model versions, performance metrics, and lineage for streamlined model registry management.
Evaluates research rigor and methodology through systematic assessment of statistical validity, biases, and evidence quality.
Implements rigorous evaluation frameworks for Large Language Model applications using automated metrics, LLM-as-judge patterns, and human feedback loops.
Optimizes machine learning model performance by automating feature creation, selection, and complex data transformations.
Queries and interprets NCBI ClinVar data to provide standardized genetic variant classifications and clinical significance evidence.
Processes and analyzes genomic data formats including BAM, VCF, and FASTA using a Pythonic interface to htslib.
Builds sophisticated Retrieval-Augmented Generation (RAG) systems to ground LLM responses with external knowledge and proprietary data.
Automates digital pathology image processing and tile extraction for whole slide images in deep learning pipelines.
Builds, optimizes, and executes quantum circuits and algorithms across various hardware providers and simulators.
Generates interactive, publication-quality scientific and statistical visualizations using the Plotly Python library.
Streamlines automated protein testing and validation through cloud-based laboratory workflows and sequence optimization tools.
Automates laboratory liquid handling by generating Python Protocol API v2 scripts for Flex and OT-2 robots.
Optimizes Large Language Model prompts to minimize token usage, reduce operational costs, and enhance response quality.
Connects Claude to the NIH Metabolomics Workbench for comprehensive access to metabolite data, study metadata, and mass spectrometry search capabilities.
Organizes and scales PyTorch code into modular, high-performance deep learning workflows with minimal boilerplate.
Manages and tracks machine learning model versions, performance metrics, and lineage directly within Claude Code.
Performs advanced materials analysis, crystal structure manipulation, and Materials Project database integration for computational scientists.
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