data science & ml Claude 스킬을 발견하세요. 61개의 스킬을 탐색하고 AI 워크플로우에 완벽한 기능을 찾아보세요.
Streamlines machine learning development by automatically generating end-to-end pipelines for model selection, tuning, and evaluation from natural language.
Navigates and queries RDC's Snowflake data warehouse for marketing, clickstream, and lead attribution analysis using built-in business logic.
Integrates Google Gemini's multimodal analysis, massive context processing, and image generation capabilities directly into Claude Code.
Performs high-performance, vectorized string manipulation and text cleaning using NumPy's specialized string modules.
Generates high-fidelity video prompts for Google's Veo 3.1 model by analyzing images and applying professional cinematic formulas.
Optimizes LLM performance and reliability through automated model selection, cost estimation, and intelligent fallback strategies.
Optimizes Text-to-Speech model training and voice cloning using the Unsloth library for faster performance and lower VRAM usage.
Implements robust multi-agent systems using Pydantic tool schemas, state management, and advanced orchestration patterns.
Programmatically creates, edits, and optimizes Jupyter and Google Colab notebooks with precise JSON formatting and metadata management.
Provides specialized technical auditing and compliance reviews for Physics-Guided GNN research papers targeting IEEE Power & Energy Society submissions.
Builds professional-grade private equity leveraged buyout (LBO) models in Excel with automated debt schedules and return analysis.
Optimizes Mem0 performance through advanced query tuning, multi-layer caching strategies, and cost-reduction patterns.
Streamlines machine learning model development with production-ready templates for classification, text generation, and parameter-efficient fine-tuning.
Optimizes embedding model selection, configuration, and cost estimation for RAG pipelines.
Implements managed Retrieval-Augmented Generation (RAG) using Google File Search and Gemini models for high-accuracy document retrieval and grounding.
Ensures the integrity of machine learning training workflows by validating datasets, model checkpoints, and system dependencies.
Calculates and compares machine learning training and inference costs across major cloud GPU platforms like Modal, Lambda Labs, and RunPod.
Sets up comprehensive monitoring dashboards using TensorBoard and Weights & Biases to track machine learning experiments in real-time.
Configures and optimizes Google Cloud Platform environments for BigQuery ML and Vertex AI training workloads.
Provides production-ready machine learning templates and training workflows for classification, text generation, and financial analysis.
Implements production-ready RAG pipelines and multi-step agent workflows using LangChain, LangGraph, and LangSmith templates.
Generates and validates recursive string diagrams using category theory primitives for complex system modeling.
Manages high-fidelity voice cloning workflows, library organization, and audio optimization for synthetic speech generation.
Integrates Large Language Model chat completions into backend applications using the z-ai-web-dev-sdk for advanced conversational AI and text generation.
Builds complex, stateful, and cyclic multi-actor AI agent workflows using the LangGraph framework.
Integrates sophisticated large language model chat completions into backend applications using the z-ai-web-dev-sdk.
Implements advanced Retrieval-Augmented Generation (RAG) workflows to build knowledge-grounded LLM applications and semantic search systems.
Provides comprehensive financial frameworks for modeling, valuation, corporate finance decisions, and advanced statement analysis.
Generates balanced, deterministic execution schedules by interleaving three color streams using GF(3) mathematical conservation.
Implements a homotopical framework for Artificial Life that treats organisms as morphisms and verifies structural changes at interaction time.
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