Data Science & ML Agent Skills

Availability Heuristic Thinking Pattern

Mitigates cognitive bias in decision-making by prioritizing statistical base rates over vivid, anecdotal evidence.

ML Model Selection Framework

Guides the selection of optimal machine learning algorithms by analyzing problem structure, data properties, and production constraints.

Thematic Analysis

Performs systematic qualitative thematic analysis on document collections to extract deep structural insights and categorized themes.

OpenAI Whisper Transcription

Transcribes audio and video files locally using the OpenAI Whisper CLI without the need for an API key.

Financial Researcher

Conducts autonomous, institutional-grade financial analysis using multi-guru perspectives and advanced composite scoring.

Agno AI Agent Framework

Build and deploy production-ready multi-agent systems with MCP integration and automated workflows.

LLM Fine-Tuning Strategies

Provides comprehensive frameworks and best practices for adapting foundation models to specialized domains using full fine-tuning and parameter-efficient methods.

AI-PRISMA Screening Assistant

Automates systematic literature screening using the PRISMA 2020 framework and cost-effective Groq LLMs.

Pareidolia Pattern Analysis

Prevents false positive pattern recognition in data and visual analysis by distinguishing genuine signals from cognitive illusions.

Clustering Illusion Analyzer

Identifies and mitigates the tendency to see meaningful patterns in random data streaks or clusters.

Survivorship Bias Thinking Pattern

Enables Claude to identify and mitigate logical errors caused by focusing on visible successes while ignoring hidden failures.

Regression to the Mean Thinking Pattern

Enhances decision-making by identifying statistical reversion in performance data and preventing false causal interpretations.

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.