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Maker
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Manual pipeline prototyping is slow and resource-heavy. I built a white-box pipeline builder to instantly benchmark classifiers, compare clustering outputs, and iterate on feature engineering in seconds.
To scale this further, I developed an AI copilot—but naive LLM+tool integration failed. I engineered a robust architecture instead: adaptive lean prompts that shift with the task, an error registry that captures and promotes proven “golden” solutions, and a RAG-accessible technical database. The copilot continuously refines itself through real usage, turning every pipeline run into a smarter, more reliable assistant.
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Maker
Announcing this new update that marks a major leap in AI adaptability and platform stability. Every clustering algorithm has been battle-tested on datasets exceeding 1 million rows with 40+ features, and fine-tuned for peak performance on our heaviest workloads: outlier detection, UMAP dimensionality reduction, and silhouette scoring
Announcing this new update that marks a major leap in AI adaptability and platform stability. Every clustering algorithm has been battle-tested on datasets exceeding 1 million rows with 40+ features, and fine-tuned for peak performance on our heaviest workloads: outlier detection, UMAP dimensionality reduction, and silhouette scoring