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。
Implements real-time machine learning architectures for processing unbounded data streams with sub-100ms prediction latency.
Transforms raw data into optimized features to improve machine learning model performance and predictive accuracy.
Combats decision-making bias by anchoring probability assessments on statistical baseline frequencies before incorporating specific case details.
Simulates complex systems from the bottom-up by defining simple rules for individual agents to observe emergent collective patterns.
Enhances decision-making by identifying statistical reversion in performance data and preventing false causal interpretations.
Enables Claude to identify and mitigate logical errors caused by focusing on visible successes while ignoring hidden failures.
Identifies and mitigates the tendency to see meaningful patterns in random data streaks or clusters.
Provides comprehensive frameworks and best practices for adapting foundation models to specialized domains using full fine-tuning and parameter-efficient methods.
Transcribes audio and video files locally using the OpenAI Whisper CLI without the need for an API key.
Guides the selection of optimal machine learning algorithms by analyzing problem structure, data properties, and production constraints.
Mitigates cognitive bias in decision-making by prioritizing statistical base rates over vivid, anecdotal evidence.
Implements production-grade deep learning training loops using battle-tested architectural patterns for optimized performance and stability.
Enables high-speed chat completions via Groq Cloud and local text embeddings through Ollama for efficient RAG workflows.
Architects reliable, production-ready AI agent workflows using constrained loops and proven reliability patterns.
Performs systematic testing of input variables to identify key drivers and assess model risk across finance, engineering, and strategy.
Corrects probability judgments by integrating statistical base rates with case-specific information to avoid common cognitive biases.
Leverages the data flywheel mental model to build compounding competitive advantages through automated machine learning and user-generated signals.
Implements continuous model updates and incremental learning patterns to handle evolving data streams without full retraining.
Predicts market price and quantity changes by analyzing the interaction between producer supply and consumer demand at equilibrium.
Implements sophisticated Retrieval-Augmented Generation architectures to ground AI responses in real-time external knowledge and eliminate hallucinations.
Identifies and mitigates the gambler's fallacy to improve decision-making in probabilistic and high-risk scenarios.
Evaluates research rigor by assessing methodology, statistical validity, and evidence quality using industry-standard frameworks like GRADE and Cochrane.
Systematically evaluates scholarly research, academic papers, and technical proposals using the peer-reviewed ScholarEval framework.
Generates publication-quality scientific diagrams and architectural schematics using smart iterative AI refinement.
Conducts systematic academic literature reviews across multiple scientific databases with verified citations and automated document generation.
Integrates Google's Gemini models directly into the terminal for one-shot Q&A, content generation, and text summarization.
Facilitates high-level scientific research through hypothesis generation, interdisciplinary analogy discovery, and methodological development.
Integrates Google Gemini CLI capabilities into Claude Code for advanced code analysis, automated refactoring, and multi-model workflows.
Automates video format conversion, audio extraction, and high-accuracy speech-to-text transcription using FFmpeg and Whisper.
Implements architectural principles for building reliable, long-running AI agents that recover gracefully from failure and maintain context integrity.
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