Compare Runs in the MLflow UI
Sort and filter experiments to find your best model.
Compare Runs in the MLflow UI is a free MLOps Academy lesson on CoddyKit — lesson 3 of 4. You can read the complete lesson below for free — then practise it hands-on in the browser with a built-in code editor and a 24/7 AI tutor. It is part of the MLOps Academy learning path, one of 4 lessons in the course, and your progress syncs across the web and the CoddyKit app.
The Runs Table
Open an experiment in the UI and you get a runs table: one row per run, with its params and metrics laid out as columns side by side.
Sort by a Metric
Click a metric column header to sort. Order by accuracy descending and your best run jumps straight to the top of the table.
Filter With a Search
Type a query in the search box to filter. Keep only the runs that match a condition, like a metric above a threshold you care about.
metrics.accuracy > 0.9 and params.max_depth = "6"Pick Which Columns Show
Too many columns? Toggle which params and metrics are visible so the table shows only the few that actually drive your decision.
Select Runs to Compare
Tick the checkboxes next to a few runs and hit Compare. MLflow opens a focused view of just those runs side by side.
The Parallel Coordinates Plot
The parallel coordinates plot draws each run as a line across params and metrics, so you can spot which settings lead to high scores.
Scatter and Contour Views
A scatter plot maps one param against a metric. It reveals trends, like accuracy rising then falling as tree depth grows.
Inspect One Run
Click any run to open its detail page. There you see every logged param, metric curve, tag, and artifact for that single execution.
Read Metric Curves
On the detail page, stepped metrics render as curves. A loss that flattens early hints you trained longer than you needed to.
Search From Code Too
You are not stuck in the browser. Use search_runs to pull matching runs into a DataFrame and analyze them programmatically.
df = mlflow.search_runs(filter_string="metrics.accuracy > 0.9")From Compare to Decision
Comparing is how you choose a winner. Sort, filter, and plot until one run clearly stands out, then move it toward production.
Quick Check
Let us check how you surface your best run in the UI.
Recap
You sorted, filtered, and plotted runs, then opened details to confirm a winner. The UI turns a pile of runs into a clear choice. ✅
Frequently asked questions
Is the “Compare Runs in the MLflow UI” lesson free?
Yes — the full text of “Compare Runs in the MLflow UI” is free to read here on the web, and the MLOps Academy course includes 4 lessons in total. To practise it interactively (a built-in code editor and a 24/7 AI tutor) and unlock the rest of the MLOps Academy course, upgrade to CoddyKit PRO.
What will I learn in “Compare Runs in the MLflow UI”?
Sort and filter experiments to find your best model. You practise MLOps Academy with hands-on code you run directly in the browser, and a 24/7 AI tutor answers your questions as you work through the lesson.
Do I need any experience to start MLOps Academy?
No prior experience is required. MLOps Academy on CoddyKit is structured for beginners through advanced learners; this is — lesson 3 of 4, so you can start here or from the beginning and move at your own pace.
How long does the “Compare Runs in the MLflow UI” lesson take?
Most CoddyKit lessons take about 5–10 minutes. Each one is bite-sized and interactive, so you make steady progress and pick up exactly where you left off across the web and the app.
Can I write and run code in this MLOps Academy lesson?
Yes. Every MLOps Academy lesson includes a built-in code editor, so you write and run real code right in your browser and get instant AI feedback — no local setup required.
All lessons in this course
- Install MLflow and Start Tracking
- Log Params, Metrics, and Artifacts
- Compare Runs in the MLflow UI
- Autolog with One Line of Code