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Neptune app overview#

Overview of the Neptune app

In the Neptune web application (UI), you can:

  • View all logged metadata in a folder-like structure.
  • Preview various data types, such as tables, images, and video.
  • Monitor your training metrics live.
  • Organize, group, and filter runs.
  • View run diffs side by side.
  • Contrast artifact metadata between runs.
  • Compare run metrics individually or as group averages.
  • Save customized views and dashboards project-wide.
  • Share persistent links with anyone.
  • Download data directly from the app.
  • Edit run descriptions and add tags.
  • Stop or abort runs directly from the app.
  • Manage your workspace and monitor usage.

How does it work?#

import neptune
from sklearn.datasets import load_wine

run = neptune.init_run()
data = load_wine()
X_train, X_test, y_train, y_test = train_test_split(...)

PARAMS = {"n_estimators": 10, "max_depth": 3, ...}
run["parameters"] = PARAMS

clf = RandomForestClassifier(**PARAMS)

test_f1_score = f1_score(y_test, y_test_pred.argmax(axis=1), average="macro")
run["test_f1"] = test_f1_score

All metadata preview

Metrics of several runs visualized as charts in Neptune

Custom dashboard with multiple metadata types

Browse examples#

Click the link to see an example in Neptune.

Component Neptune example     Description & docs
Runs table View in Neptune ≫ The metadata of the runs organized in a table view. You can customize and save table views for later.
Comparison of runs View in Neptune ≫ Comparison view of selected runs. Contrast the metadata in different ways by switching between the dashboards.
Logged metrics View in Neptune ≫ Series of values are auto-displayed as charts.
Logged hardware consumption View in Neptune ≫ Neptune logs hardware consumption metrics by default.
Logged interactive charts View in Neptune ≫ You can display charts generated with plotting libraries in an interactive way.
Logged images View in Neptune ≫ Preview any uploaded images.
Custom dashboard View in Neptune ≫ You can combine different metadata types and widgets in a single view by creating custom dashboards.