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 long-running AI agent sessions by implementing structured context compression to maintain technical accuracy and memory efficiency.
Integrates Claude with the FinnHub API to retrieve real-time stock quotes, fundamental data, crypto prices, and market news.
Implements production-grade prompt engineering patterns, RAG optimization, and agentic system architectures for advanced AI products.
Empowers autonomous AI agents with real-time X (Twitter) search, web search, and sandboxed Python code execution capabilities.
Processes and analyzes billion-row tabular datasets using lazy, out-of-core DataFrame operations without exceeding available RAM.
Builds and deploys serverless bioinformatics workflows on the Latch platform using Python-native SDKs.
Deploys and orchestrates cloud-based AI agent swarms with event-driven workflow automation and intelligent coordination.
Standardizes Python experiment layouts, stage entrypoints, and asset handling for consistent data science workflows.
Orchestrates multi-agent swarms using dynamic topologies and automated task distribution for complex, parallel AI workflows.
Queries the ClinicalTrials.gov API v2 to search, filter, and export detailed clinical study data for research and patient matching.
Searches and retrieves life sciences preprints from the bioRxiv database with advanced filtering and PDF download capabilities.
Implements adaptive learning and pattern recognition systems to enable AI agents to optimize strategies and improve through experience.
Builds and manages semantic knowledge graphs to enhance autonomous coding and project understanding.
Implements high-performance adaptive learning patterns and trajectory tracking for self-learning agents using a 150x faster vector database.
Accesses and queries the world's largest database of somatic mutations and curated cancer genes for research and precision oncology.
Implements and trains reinforcement learning algorithms to create autonomous agents that improve through experience.
Accelerates genomic interval analysis and machine learning preprocessing with high-performance Rust-powered algorithms and Python bindings.
Trains and deploys reinforcement learning models for autonomous agents using nine specialized algorithms including Decision Transformers and Q-Learning.
Implements adaptive learning systems to enable AI agents to recognize patterns, optimize strategies, and improve continuously through experience.
Deploys and trains sophisticated neural networks across distributed sandbox environments using various architectures and federated learning techniques.
Accesses the world's largest database of somatic mutations for cancer research and precision oncology data analysis.
Implements high-performance persistent memory and reasoning patterns for AI agents using vector storage and reinforcement learning.
Implements high-performance adaptive learning and experience replay patterns for self-improving AI agents using a high-speed vector database backend.
Queries and analyzes openFDA regulatory data for drugs, medical devices, food safety, and substance identification.
Analyzes mass spectrometry data for proteomics and metabolomics using the PyOpenMS library.
Integrates Google's Gemini 3 Pro API into Python and Node.js applications with advanced reasoning and streaming capabilities.
Builds high-performance Retrieval-Augmented Generation (RAG) systems using vector databases, semantic search, and advanced retrieval patterns.
Connects Claude to over 600 specialized scientific tools and databases for bioinformatics, drug discovery, and genomic analysis.
Integrates Claude with the DNAnexus platform to develop genomics apps, manage sequencing data, and orchestrate bioinformatics pipelines.
Performs high-performance genomic interval analysis and data preprocessing for machine learning using Rust-powered tools.
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