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。
Analyzes single-cell omics data using deep generative models for tasks like batch correction, integration, and differential expression.
Analyzes, transcribes, and edits video files using AI-powered frame extraction, local speech-to-text, and multi-modal audio understanding.
Optimizes AI prompts by applying architecture-specific techniques for autoregressive and reasoning-based models.
Implements high-performance, secure text-to-speech synthesis using Kokoro TTS for real-time voice applications.
Monitors financial markets autonomously to generate AI-driven trading signals using multi-agent consensus and the Stirrup framework.
Automates the lifecycle of LLM fine-tuning workloads on RunPod GPU instances using the Unsloth framework.
Automates the generation of professional model cards and the deployment of fine-tuned LLMs to the Hugging Face Hub.
Transforms complex business data into actionable insights and strategic recommendations using modern BI tools and predictive analytics.
Simplifies the deployment and management of Unsloth fine-tuning jobs on Hugging Face cloud GPUs.
Manages local GPU fine-tuning workflows using Unsloth to optimize LLM training performance and resource utilization.
Generates optimized training notebooks and scripts for fine-tuning LLMs using the Unsloth framework.
Optimizes AI agent memory searches by classifying query intent and routing requests through the most efficient retrieval layers.
Provides a comprehensive C/C++ API reference and implementation patterns for high-performance local LLM inference using llama.cpp.
Provides a comprehensive reference for developing native C extensions and GCL applications within the GreyCat ecosystem.
Orchestrates complex memory search operations by classifying query intent and routing requests through optimal retrieval layers.
Analyzes and maps semantic themes within agent memory using time-decayed importance scoring to surface relevant conversation patterns.
Enables semantic similarity and hybrid keyword-vector search across agent memory for intelligent information retrieval.
Synthesizes fragmented research findings into coherent, structured narratives with evidence-based uncertainty quantification.
Configures and optimizes LLM providers for agent-memory summarization with automated model discovery and cost estimation.
Optimizes agent memory searches by automatically classifying query intent and routing requests through the most efficient retrieval layers.
Provides expert guidance and automated tools for statistical modeling, experiment design, causal inference, and production-grade machine learning pipelines.
Integrates local Large Language Models using llama.cpp and Ollama while implementing robust security measures against prompt injection and resource-based attacks.
Extracts and visualizes semantic topic patterns from agent conversation history using time-decayed importance scoring.
Implements high-performance, privacy-preserving wake word detection for always-listening voice assistants using openWakeWord and test-driven development.
Optimizes Large Language Models through 4-bit and 8-bit quantization to enable efficient deployment on resource-constrained hardware.
Automates the creation, editing, and analysis of professional Excel spreadsheets with advanced formula support and data visualization.
Maps and analyzes semantic themes within agent memory using time-decayed importance scoring to discover conversational patterns.
Automates systematic literature reviews for sociology and academic research using the OpenAlex API and structured screening workflows.
Optimizes CUDA and GPU computing development with performance-focused guardrails and industry-standard implementation patterns.
Automates the setup, validation, and execution of phylogenetic ancestral range reconstruction using BioGeoBEARS in R.
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