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 industry-standard gradient boosting algorithms for high-performance machine learning on tabular and structured datasets.
Translates CODEX/Akoya experiment.json metadata into the KINTSUGI ExperimentConfig format with precise field and wavelength mapping.
Optimizes large-scale data staging on HPC environments using rsync, bash, and SLURM to ensure data integrity and script reliability.
Evaluates AI alignment and protocol adherence through the Joseph Cognitive Baseline v2.1 test suite.
Automates professional spreadsheet creation, data analysis, and financial modeling with rigorous formula integrity and industry-standard formatting.
Integrates Google's Gemini models into the Claude Code workflow to handle massive context windows and multimodal file processing.
Synchronizes and caches comprehensive Charles Schwab market data, including account status, real-time quotes, and option chains for trading agents.
Automates Google Vertex AI multimodal operations to process, analyze, and transform media content within your development environment.
Leverages Google Gemini API to process and analyze audio, video, images, and documents directly within Claude.
Analyzes and classifies the emotional tone of text data into positive, negative, or neutral categories for rapid opinion mining.
Architects high-impact system prompts to define agent identity, rules, and behavior patterns for custom AI assistants.
Translates trading strategy documentation into production-ready Python backtesting code and TradingView Pine Script.
Orchestrates AI execution phases to ensure deterministic outputs and efficient resource management within AGI environments.
Screens and analyzes stocks using quantitative multi-factor models to identify high-potential investment opportunities.
Builds robust Retrieval-Augmented Generation (RAG) pipelines for grounded AI responses using vector stores and embeddings.
Builds sophisticated AI agents with tool-calling capabilities and multi-provider LLM integration using a Kotlin-native framework.
Manages KINTSUGI project initialization by distinguishing between raw and processed data while automating SLURM configuration.
Guides users through a comprehensive 10-step pipeline for processing multiplex imaging data on SLURM-managed HPC clusters.
Maximizes HPC throughput by orchestrating concurrent GPU and CPU batch processing across multiple SLURM accounts.
Optimizes large language models to communicate natively through the Slipstream inter-agent protocol using efficient finetuning workflows.
Streamlines AILANG programming for AI agents by providing real-time syntax rules, capability-based execution, and a searchable library of 90+ code examples.
Provides standardized, type-safe result schemas for Synapse SDK plugin actions to ensure consistent data output and validation.
Streamlines the creation of Synapse plugin actions using function-based and class-based patterns with built-in Pydantic validation.
Streamlines Machine Learning workflows with specialized base classes for training, inference, data export, and deployment.
Converts incompatible image, video, and audio formats into supported extensions for seamless data collection uploads.
Applies structured self-analysis and governance protocols to evaluate and validate AI decision-making processes.
Streamlines complex file uploads and metadata mapping to Synapse data collections across local and cloud storage providers.
Facilitates the programmatic execution and discovery of Synapse plugins across local and distributed environments.
Solves overdetermined algebraic, ODE, and PDE systems using the CRACK package in the REDUCE computer algebra system.
Guides developers in configuring Synapse plugin metadata, action definitions, and runtime environments for seamless tool integration.
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