发现data science & ml类别的 Claude 技能。浏览 53 个技能,找到适合您 AI 工作流程的完美功能。
Provides expert methodological guidance and implementation patterns for conducting rigorous Simulated Treatment Comparisons (STC) in clinical trial analysis.
Streamlines scientific development on HPC environments using multi-root workspaces and automated test data extraction.
Automates hyperparameter tuning and model selection using intelligent search strategies like Bayesian optimization.
Manages complex Excel workbooks with automated formula creation, financial modeling standards, and data analysis.
Generates cinematic video transitions and morphing animations between two keyframe images using Google’s Veo 3.1 via fal.ai.
Automates complex time-series forecasting pipelines including trend analysis, seasonality detection, and multi-model predictions.
Empowers AI agents with adaptive learning and pattern recognition to optimize workflows and decision-making strategies through experience.
Provides expert methodological guidance and implementation patterns for Multilevel Network Meta-Regression (ML-NMR) in evidence synthesis.
Configures Google ADK bidirectional streaming to build low-latency, multimodal AI agents with real-time voice and video capabilities.
Integrates multiple LLM providers using isolated interfaces and normalized data structures for consistent AI implementation.
Constructs sophisticated, stateful AI agent workflows and graph-based logic using LangGraph best practices.
Optimizes LangGraph agent architectures by implementing explicit state management, granular node design, and robust transition patterns.
Integrates multiple LLM providers like Anthropic, OpenAI, and Google Gemini into applications using advanced orchestration and reasoning patterns.
Train, deploy, and manage distributed neural networks across sandboxed E2B environments using multiple architectures and federated learning.
Implements persistent, high-performance memory and learning patterns for AI agents using AgentDB.
Implements and trains autonomous agents using nine specialized reinforcement learning algorithms for self-improving behavior.
Optimizes and crafts high-performance LLM prompts using research-backed techniques like Chain-of-Thought and Few-Shot learning.
Automates the creation, formatting, and analysis of professional-grade Excel spreadsheets and financial models.
Implements high-performance persistent memory systems for AI agents to enable long-term context retention and autonomous pattern learning.
Implements robust Retrieval-Augmented Generation (RAG) pipelines including document ingestion, hybrid search, reranking, and intelligent query routing.
Automates the creation, editing, and analysis of professional-grade Excel spreadsheets and financial models with dynamic formulas and rigorous verification.
Implements Retrieval-Augmented Generation (RAG) systems with vector databases and semantic search to build grounded, knowledge-aware AI applications.
Optimizes local LLM orchestration and GPU performance for Ollama-integrated AI environments.
Automates the creation, editing, and analysis of professional Excel spreadsheets with advanced formula support and industry-standard financial modeling.
Analyzes protein and molecular structures through AlphaFold interpretation, quality validation metrics, and comparative structural techniques.
Analyzes legacy Thai DBF accounting databases by converting them to Parquet for high-performance DuckDB querying.
Manages and routes requests across multiple AI providers including Anthropic, Ollama, and HuggingFace.
Streamlines the development of AI-powered features within the Moodle LMS using the official AI Subsystem for version 4.5 and above.
Implements high-performance adaptive learning patterns and trajectory tracking for self-learning agents using a 150x faster vector database.
Provides R-based statistical methods and best practices for clinical trial design, analysis, and regulatory reporting.
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