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。
Implements and trains reinforcement learning algorithms to create self-improving autonomous agents using the AgentDB plugin system.
Implements adaptive learning and experience replay for agents using a high-performance vector database to optimize decision-making over time.
Orchestrates intelligent agent swarms, manages secure code sandboxes, and handles application deployment within the Flow Nexus ecosystem.
Generates high-quality speech from text locally using Sherpa-ONNX models without requiring cloud connectivity.
Generates professional, accessible, and insightful data visualizations using Python's leading charting libraries like Matplotlib and Seaborn.
Synthesizes raw qualitative and quantitative research into actionable product insights and prioritized opportunity areas.
Applies advanced statistical methods to analyze data distributions, detect trends, and validate hypotheses with scientific rigor.
Automates quality control and filtering for single-cell RNA sequencing data following scverse and scanpy best practices.
Profiles datasets and assesses data quality to discover patterns and understand schemas before analysis.
Standardizes laboratory instrument data by converting various file formats into the Allotrope Simple Model (ASM) for LIMS and downstream analysis.
Automates the deployment and management of nf-core bioinformatics pipelines for genomic data analysis.
Generates tailored data analysis skills by capturing tribal knowledge, schema details, and business metrics from analysts.
Performs advanced deep learning analysis for single-cell genomics using the scvi-tools framework.
Validates data analysis methodology, accuracy, and documentation to ensure high-quality, reproducible insights for stakeholders.
Queries and downloads large-scale public cancer imaging datasets from the NCI Imaging Data Commons using Python and SQL.
Queries the FRED API for over 800,000 economic time series to support macroeconomic research and financial analysis.
Automates the end-to-end process of converting literary works into high-quality datasets for fine-tuning AI models on specific authorial voices and writing styles.
Optimizes AI context window usage through strategic compression, observation masking, and partitioning to improve performance and reduce costs.
Guides the architectural design, evaluation, and implementation of LLM-powered applications and agent systems.
Provides foundational principles and implementation patterns for managing language model context windows and attention mechanics in AI agent systems.
Models autonomous agent behaviors using Belief-Desire-Intention (BDI) architecture and formal cognitive ontologies.
Optimizes AI agent token usage through advanced context summarization and structured information preservation.
Design and implement sophisticated agent memory architectures, from vector stores to temporal knowledge graphs, for cross-session persistence.
Diagnoses and mitigates context-related failures in agent systems to ensure reliable performance across large context windows.
Implements sophisticated LLM-as-a-judge frameworks and evaluation rubrics to ensure production-grade quality and bias mitigation.
Designs and implements sophisticated multi-agent architectures for Claude Code by optimizing context isolation and coordination strategies.
Extracts structured text, metadata, and tables from over 75 document formats using a high-performance Rust core.
Connects Claude to the K-Dense Web platform for advanced, end-to-end scientific research workflows and multi-agent AI collaboration.
Performs advanced numerical computing, matrix operations, and scientific visualizations using MATLAB and GNU Octave syntax.
Automates advanced quantum chemistry workflows and protein-ligand modeling using a cloud-based Python API.
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