Results for “mapulus”

Evaluates computational throughput and real-time efficiency of embedded CPU and GPU platforms by measuring peak FLOPS via a matrix rotation kernel and assessing inference latency and power consumption on a robotic vision pipeline.

Guides analysis of Neuropixels recordings from raw data to curated units, covering preprocessing, motion correction, spike sorting, quality metrics, and export.

Globus CLI workflow for staging HuBMAP CODEX datasets from remote endpoints to HiPerGator

Scores generated image captions against reference captions and source images using the Polos metric, which is trained to align with human judgments and probes hallucination robustness and open-vocabulary evaluation.

Enforces ML infrastructure, experiment tracking, reproducibility, model packaging, CI/CD, monitoring, and infrastructure-as-code standards at principal-engineer level.

MLOps Engineer IA — Expert en déploiement de modèles ML (A/B testing, feature stores, MLflow, Kubeflow). Industrialise le ML du notebook à la production.

Process and analyze mass spectrometry data with the Matchms Python library, including importing spectra, filtering peaks, calculating similarity scores, and building reproducible analytical workflows.

Run ML workloads on Modal's serverless GPU cloud platform with auto-scaling, pay-per-second pricing, and Python-native infrastructure.

Run ML workloads on Modal's serverless GPU cloud: deploy models as auto-scaling APIs, run batch jobs, and schedule tasks with pay-per-second GPU pricing.

Diagnose and fix macOS resource pressure for Claude Code workflows. Use when load avg is high, swap is saturated, CC feels slow, or before spinning up parallel agents/worktrees. Covers CPU top-talkers, swap pressure, zombie claude processes, Node heap tuning, Spotlight/background-agent pruning, and purge. Apple Silicon aware.

Set up MoonPay as an MCP server for Claude Desktop or Claude Code. Provides all MoonPay CLI tools via the Model Context Protocol.

CC-Panes bundled skill: Spec 工作流