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Data & AI

Build comprehensive ML pipelines, experiment tracking, and model registries with MLflow, Kubeflow, and modern MLOps tools.

Data & AI

Orchestrate end-to-end ML pipelines with Prefect/Airflow: DAGs, dependencies, retry, scheduling, monitoring, and integration with MLflow, DVC, and feature stores.

Data & AI

Scaffolds matplotlib figure code following established TDA visualization conventions. Uses predefined style constants for consistent publication-ready figures.

Data & AI

Converts JSON, YAML, XML, and CSV data into token-efficient formats like TSV, TOON, and YAML, reducing token usage by 30-70% for LLM inputs. Supports filtering by paths, limiting nesting depth, and truncating arrays to fit context windows. Useful for minimizing token consumption when feeding structured data to language models.

Data & AI

Scaffold matplotlib code for publication-quality TDA figures following project conventions. Provides templates for persistence diagrams, barcodes, null histograms, and landscape comparisons.

Data & AI

Build and maintain a personal knowledge base using LLMs, with raw/ and wiki/ directories.

Data & AI

Build scalable data pipelines and modern data warehouses. Implements Apache Spark, dbt, Airflow, and cloud-native platforms.

Data & AI

Orchestrate end-to-end ML pipelines using Prefect or Airflow with DAG construction, retry logic, scheduling, and monitoring.

Data & AI

Implement data quality validation with Great Expectations, dbt tests, and data contracts. Use for building quality pipelines and establishing data contracts.

Data & AI

Prepares files for NotebookLM by scoring and merging sources, converting formats, and optimizing RAG retrieval within the 50-source limit.

Data & AI

Create interactive data visualizations using D3.js. Use this when creating charts, graphs, network diagrams, geographic visualizations, or custom SVG-based data visualization.

Data & AI

Run 150+ AI apps including image generation, video creation, LLMs, search, and more via the inference.sh CLI. No GPU required.