Data Science & ML Claudeスキル

Agent-Based Modeling Simulation

Simulates complex systems from the bottom-up by defining simple rules for individual agents to observe emergent collective patterns.

Jupyter Notebook Manager

Programmatically creates, edits, and optimizes Jupyter and Google Colab notebooks with precise JSON formatting and metadata management.

ML Batch Processing Pattern

Implements a decoupled architecture for pre-computing machine learning predictions at scheduled intervals to optimize costs and serving latency.

Base Rate Analysis

Combats decision-making bias by anchoring probability assessments on statistical baseline frequencies before incorporating specific case details.

Research & Statistical Analysis

Performs hypothesis-driven statistical analysis and data visualization on datasets, system metrics, and experiment logs.

Haipipe NN Algorithm Layer

Standardizes the integration of external machine learning libraries and custom neural network modules within the Haipipe architecture.

Notebook Analysis Pipeline

Manages a robust four-stage pipeline that converts modular Python scripts into interactive Jupyter notebooks and comprehensive markdown documentation.

HAIPipe Source Data Processor

Standardizes raw academic and medical data files into structured SourceSet DataFrames for research pipelines.

Megatrends Analysis

Identifies long-term societal and structural shifts through bottom-up pattern detection and massive data aggregation.

Haipipe Model Instance Layer

Orchestrates model lifecycles and provides HuggingFace-style APIs for modular neural network research pipelines.

HAIPipe NN Pipeline Overview

Provides a foundational architecture map and decision guide for managing neural network pipelines within the HAIPipe research framework.

Haipipe NN Model Tuner

Standardizes machine learning algorithm implementation through a universal wrapper contract for seamless training, inference, and serialization.

HaiPipe Record Processor

Transforms raw source datasets into temporally-aligned structured record sets for academic research and machine learning.

Machine Learning Engineer

Builds, trains, and deploys predictive machine learning models with robust preprocessing and standardized evaluation pipelines.

Feature Engineering Patterns

Transforms raw data into optimized features to improve machine learning model performance and predictive accuracy.

D3.js Data Visualization

Creates sophisticated, interactive data visualizations and custom charts using the D3.js library.

Streaming Inference

Implements real-time machine learning architectures for processing unbounded data streams with sub-100ms prediction latency.

Popper's Falsifiability

Validates hypotheses and scientific theories by ensuring they are testable and capable of being proven false through rigorous experimentation.

Forecasting Calibration & Discrimination

Optimizes predictive accuracy by balancing probability alignment with the ability to distinguish between diverse outcomes.

Natural Selection Design Patterns

Implements evolutionary design principles to build adaptive systems that improve through iterative variation, selection pressure, and inheritance.

Deep Research Oracle

Routes prompts and code context to multiple high-performance AI models for cross-validation and specialized deep research.

Prompt Engineering Frameworks

Applies systematic techniques and structured frameworks to optimize LLM instructions for maximum accuracy, consistency, and output quality.

Evolution Patterns

Applies biological adaptation principles to optimize complex systems through iterative variation, selection, and inheritance.

Base Rate Thinking Pattern

Anchors predictions and decision-making in statistical frequencies to avoid cognitive bias and improve estimation accuracy.

Aristotle Mathematical Prover

Formalizes natural language mathematical questions into Lean 4 and verifies them using the Harmonic Aristotle prover API.

Tournament Forecasting

Implements structured competitive prediction frameworks using Brier scores and systematic debiasing to enhance organizational forecasting accuracy.

ctrlsys Control Theory & Systems Engineering

Simplifies the design and analysis of complex control systems using the C11-based ctrlsys library.

Fitness Landscapes Thinking Pattern

Analyzes complex optimization problems using evolutionary landscape metaphors to identify local traps and global optima.

RAG Engineer

Optimizes Retrieval-Augmented Generation architectures through advanced semantic chunking, hybrid search strategies, and vector embedding pipelines.

ML Streaming Inference Pattern

Implements real-time machine learning prediction patterns for high-throughput data streams with sub-second latency.