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Skills IA blockchain scientific computing

Découvrez les skills blockchain scientific computing, comparez leurs dépôts et consultez leurs instructions.

Catégories: blockchain scientific computing

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GitHub

nixtla-anomaly-detector

intent-solutions-io

Detects anomalies in time series data using TimeGPT. Identifies outliers, level shifts, and trend breaks without model training. Use when identifying anomalies, outliers, or unusual patterns in time series. Tri...

GitHub

nixtla-event-impact-modeler

intent-solutions-io

Quantifies the impact of exogenous events on contract prices using TimeGPT and CausalImpact. Triggers on "event impact analysis", "model event effects", "quantify event impact", or "causal analysis".

GitHub

nixtla-research-assistant

intent-solutions-io

Research and summarize Nixtla ecosystem updates and time-series forecasting content from the web and GitHub. Use when gathering release notes, recent changes, or best-practice references. Trigger with "Nixtla u...

GitHub

julia-development

seabbs

Expert guidance for Julia package development following SciML standards, Distributions.jl patterns, and Julia ecosystem best practices

GitHub

td-fft

teradata-labs

Fast Fourier Transform for frequency domain analysis and spectral decomposition

GitHub

openai-deep-research

closedloop-technologies

Use OpenAI's Deep Research API (o3 / o4 models) to automate multi-step, citation-backed research workflows.

Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.

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