Discover Agent Skills for data science & ml. Browse 61 skills for Claude, ChatGPT & Codex.
Analyzes asset price deviations from long-term exponential trends to identify historical extremes and macro market regimes.
Implements robust Retrieval-Augmented Generation (RAG) systems for LLM applications using vector databases and semantic search.
Analyzes Japanese Government Bond (JGB) transaction data to identify record-breaking selling flows from insurance companies.
Implements high-performance adaptive learning and trajectory tracking for self-improving AI agents using AgentDB's ultra-fast vector backend.
Trains and deploys complex neural networks within distributed E2B sandboxes for scalable machine learning workflows.
Architects sophisticated LLM applications using LangChain with advanced agent patterns, persistent memory, and modular tool integrations.
Empowers AI agents with persistent, high-performance memory and learning patterns using AgentDB and ReasoningBank.
Routes users to the most effective reinforcement learning algorithms and implementation patterns based on specific problem characteristics.
Standardizes the implementation of data validation, risk limits, and compliance contracts within the OptAIC framework.
Quantifies time series forecast uncertainty using conformal prediction to generate reliable prediction intervals and confidence bands.
Automates the creation, editing, and analysis of professional-grade Excel spreadsheets and financial models with dynamic formulas and rigorous verification.
Builds, trains, and evaluates supervised learning classification models to predict categorical outcomes from labeled datasets.
Automates the creation, formatting, and analysis of professional-grade Excel spreadsheets and financial models.
Optimizes and crafts high-performance LLM prompts using research-backed techniques like Chain-of-Thought and Few-Shot learning.
Generates professional plots, charts, and graphs automatically by analyzing data structures and selecting the optimal visualization type.
Constructs sophisticated, stateful AI agent workflows and graph-based logic using LangGraph best practices.
Integrates multiple LLM providers using isolated interfaces and normalized data structures for consistent AI implementation.
Performs advanced natural language processing to extract insights, sentiment, and key topics from text data.
Configures Google ADK bidirectional streaming to build low-latency, multimodal AI agents with real-time voice and video capabilities.
Automates complex time-series forecasting pipelines including trend analysis, seasonality detection, and multi-model predictions.
Automates hyperparameter tuning and model selection using intelligent search strategies like Bayesian optimization.
Provides expert methodological guidance and implementation patterns for conducting rigorous Simulated Treatment Comparisons (STC) in clinical trial analysis.
Implements robust evaluation frameworks for Large Language Model applications using automated metrics, human feedback, and statistical testing.
Generates text-based visualizations and comprehensive reports to analyze the relationship between typographic errors and semantic drift in experimental data.
Provides expert guidance for conducting and reviewing Matching-Adjusted Indirect Comparisons (MAIC) in clinical data analysis.
Optimizes GPU VRAM usage through OOM retry logic, idle auto-unloading, and inter-service memory coordination protocols.
Builds and analyzes phylogenetic trees using distance-based, maximum likelihood, and Bayesian inference methods.
Orchestrates end-to-end MLOps pipelines from data preparation and model training to production deployment and monitoring.
Implements professional-grade trend-following strategies, volatility targeting, and multi-scale momentum indicators for financial data analysis.
Refactors Scikit-learn and machine learning code into production-ready pipelines that ensure reproducibility and prevent data leakage.
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