Discover Agent Skills for data science & ml. Browse 61 skills for Claude, ChatGPT & Codex.
Builds and validates the three-level Gioia data structure for systematic qualitative research analysis and academic publication.
Enforces qualitative research integrity through automated rule generation, saturation tracking, and workspace branching for Claude Code.
Converts audio recordings, PDFs, and diverse document formats into structured markdown for qualitative research and AI analysis.
Automates the retrieval of training and test data dependencies from S3 for local machine learning model development and backtesting.
Captures and stores failed Hotvect command invocations as executable shell scripts for seamless debugging and reproduction.
Converts audio recordings, PDFs, and diverse document formats into structured markdown for qualitative research and AI-assisted analysis.
Automates the retrieval of SageMaker backtest results from Amazon S3 for local analysis and performance comparison.
Streamlines the configuration and validation of Hotvect algorithm training runs for Vowpal Wabbit.
Builds, optimizes, and deploys production-grade neural networks using PyTorch, TensorFlow, and modern transformer architectures.
Automates production-grade ETL pipelines and data orchestration using industry-standard tools like Airflow, dbt, and Prefect.
Generates structured evidence synthesis matrices to organize, compare, and analyze research data across multiple studies.
Generates publication-quality data visualizations and scientific figures following academic design and statistical best practices.
Generates standardized PRISMA 2020-compliant flow diagrams to document the study selection process in systematic literature reviews.
Evaluates the robustness of research findings by testing how conclusions change under varying analytical assumptions and data conditions.
Synthesizes complex findings from multiple sources into coherent, actionable conclusions with uncertainty quantification.
Facilitates visual agent design and advanced reasoning configuration for building sophisticated, multi-step AI workflows.
Provides standardized C++20 implementations for high-performance numerical computing, matrix operations, and parallel I/O.
Implements high-performance persistent memory and pattern learning for stateful AI agents using AgentDB.
Implements high-performance semantic vector search and intelligent document retrieval for RAG systems and context-aware applications.
Automates high-fidelity PDF and document conversion by selecting the optimal parsing method for academic and qualitative research data.
Implements high-performance persistent memory and pattern learning for stateful AI agents using AgentDB.
Implements adaptive learning and meta-cognitive capabilities to help AI agents optimize strategies and recognize patterns through experience.
Implement high-performance adaptive learning and memory distillation for autonomous agents using AgentDB's ultra-fast vector architecture.
Optimizes agent orchestration by integrating agentic-flow@alpha to reduce code redundancy and boost performance via Flash Attention and AgentDB.
Optimizes distributed AI systems with sub-millisecond QUIC synchronization, hybrid vector search, and advanced multi-database management patterns.
Integrates nine reinforcement learning algorithms to build autonomous, self-improving AI agents within the Claude ecosystem.
Unifies fragmented AI memory systems into a high-performance AgentDB backend featuring HNSW vector search.
Implements ultra-fast semantic vector search and intelligent document retrieval for RAG systems and knowledge bases.
Architects and optimizes high-performance distributed data pipelines for petabyte-scale workloads using Apache Spark and modern table formats.
Trains and deploys distributed neural networks using E2B sandboxes and Flow Nexus orchestration.
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