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📊 Matplotlib, Plotly, or Power BI?

A 3D dashboard bench comparing Matplotlib, Plotly and Power BI as a live metric stream from a model flows into three visualization stations.

AI & Machine Learning3DAdvanced60 FPS

A live stream of ML monitoring metrics flows from a central model node into three 3D dashboard stations — Matplotlib, Plotly and Power BI — so you can see how each tool's update cadence and visual language shapes what the same data communicates.

🔬 What It Demonstrates

The same accuracy metric is rendered three ways: a batch-refreshed static figure, a continuously live interactive chart with a crosshair, and an aggregated executive KPI/gauge summary — illustrating why the choice of tool depends on audience and refresh needs, not just aesthetics.

🎮 How to Use

Adjust the metric stream rate and the Matplotlib refresh interval, pick a focus audience to spotlight a station, and inject a drift/anomaly burst to watch how fast each visualization surfaces the problem.

💡 Did You Know?

Many production ML teams run Matplotlib, Plotly-style dashboards and BI tools like Power BI in parallel — one for reproducible offline reports, one for live debugging, and one for stakeholder-facing summaries.

⚙ Under the hood

A 3D dashboard bench comparing Matplotlib, Plotly and Power BI as a live metric stream from a model flows into three visualization stations.

machine learningdata visualizationdashboardspythonplottingvisualizationThree.js

3D · Three.js / WebGL renderer · 60 FPS target · runs fully client-side, no install