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Project

As explained in Machine Learning Platform Engineering

An Evidently project is an organizational container for dashboard configuration, data snapshots, and monitoring results.

An Evidently project organizes dashboard configuration, data snapshots, and monitoring results for one monitored ML system. It lives inside a workspace, which groups projects and their logs. section 6.2.1

A project supports a production monitoring workflow:

  • Associate repeated data snapshots with the project to compare monitoring results over time. section 6.2.1
  • Configure dashboard panels that display titles, counters, plots, and measurements such as drifted-feature share. section 6.2.1

Create an income-classifier project

Connect to the Evidently UI with RemoteWorkspace, then create a named project with an operational description: name="income-classifier", description="Used to classify users into multiple income bands".

How Machine Learning Platform Engineering covers it

How deep it goes
Explains workspace placement, project creation, snapshots, and dashboard panels, but stops short of detailing complete dashboard assembly.
Examples
Uses an income-classifier project with JSON snapshots and counters for dashboard titles and drifted-feature share.
What it assumes
Assumes familiarity with data snapshots and monitoring reports while introducing workspace and project organization.
What you can do after
Operate/configure an Evidently workspace by creating a project and adding monitoring dashboard panels.
How it connects
Connects workspaces, data snapshots, monitoring reports, dashboard panels, and data drift detection.

Related concepts

This explainer was generated by Manning's knowledge graph from the text of Machine Learning Platform Engineering. The section links point to the parts of the book it draws on.