data science & ml向けのClaudeスキルを発見してください。61個のスキルを閲覧し、AIワークフローに最適な機能を見つけましょう。
Streamlines the creation, manipulation, and visualization of multidimensional histograms using the scikit-hep Python ecosystem.
Provides a rapid diagnostic summary of Sparse Autoencoder (SAE) features to generate research hypotheses and identify model behaviors.
Detects structural breaks and regime shifts in financial time-series using Gaussian Process models to identify market transitions.
Generates standardized Jupyter notebooks for fantasy football data analysis, integrating DuckDB connections, dbt mart queries, and professional visualization patterns.
Categorizes text, detects sentiment, and filters spam using pre-trained and custom-trained machine learning models.
Ranks and filters retrieved documents based on vector similarity metrics to optimize RAG pipeline relevance.
Executes structured, atomic tasks for fantasy football analytics, FASA optimization, and trade intelligence within a standardized sprint framework.
Extracts Vehicle Identification Numbers (VIN) from images and photos using advanced OCR technology.
Explains and implements core Transformer architecture components for LLM development, fine-tuning, and model analysis.
Evaluates LLM outputs and optimizes prompts using Evidently.ai metrics and LLM-as-a-judge patterns.
Optimizes LLM fine-tuning using LoRA, QLoRA, and Unsloth to drastically reduce memory requirements and accelerate training cycles.
Provides a clean, Pythonic interface for interacting with Ollama to handle text generation, chat completions, and model management.
Aligns AI models with human preferences using Direct Preference Optimization to improve reasoning and response quality without explicit reward models.
Optimizes large language models for efficient inference and training using various precision types and memory estimation techniques.
Streamlines the supervised fine-tuning of Large Language Models using Unsloth for optimized performance and reasoning model development.
Simplifies building LLM-powered applications by providing standardized abstractions for prompt engineering, model orchestration, and structured output parsing.
Manages local Ollama inference servers using Podman Quadlet to provide GPU-accelerated LLM capabilities.
Deploys and manages ComfyUI instances for node-based Stable Diffusion image generation with GPU acceleration and model lifecycle support.
Implements Reinforcement Learning with Leave-One-Out estimation to stabilize model training and optimize policy performance.
Provides comprehensive Bayesian meta-analysis templates using Stan and JAGS for advanced biostatistical evidence synthesis.
Streamlines the creation and management of reactive marimo notebooks for interactive data science and analytics workflows.
Inspects Marimo notebook execution results and HTML snapshots to debug errors and verify cell outputs.
Deploys and manages reactive Python notebooks with hot-reloading capabilities for interactive development.
Predicts age, gender, and ethnicity from person data and images to enrich datasets and customer profiles.
Deploys and optimizes serverless AI models, embedding generation, and RAG architectures directly on Cloudflare’s edge network.
Orchestrates comprehensive meta-analysis workflows with multi-gate validation to ensure data integrity and statistical accuracy.
Analyzes and extracts deep insights from video files and YouTube URLs using the Google Gemini API.
Optimizes Apache Spark data processing jobs through advanced partitioning, memory management, and shuffle tuning.
Automates the archival and quality classification of algorithmic trading models based on performance metrics and risk thresholds.
Builds cost-free RAG systems using parallel document processing and local vector embeddings.
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