Dashboard
Experiment tracking for
machine learning models
W&B for ML Experiment Tracking
Get started with a quick overview of the Dashboard and how to track and visualize using our tools for machine learning experiment tracking.
OVERVIEW
Machine learning experiment tracking
Why is experiment tracking so important for doing real world machine learning? Here's a quick overview of the problem and tools.
TUTORIAL
Quickstart guide to ML experiment tracking
Get started tracking model results in 5 minutes, and visualize your machine learning models easily with Weights & Biases.
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Features

Fast Integration

Add just a few lines of code to your script to get the power of W&B logging.
We're framework agnostic.

import torch
import torch.nn as nn
from torchvision import datasets
import wandb

wandb.init()
...

Log Anything

Easily log metrics from your script to visualize results in real time as your model trains.

wandb.log({"acc": accuracy, "val_acc": val_accuracy})

Explore Everything

Peek under the hood and see what your model is producing at each time step.

wandb.log({"point_cloud": wandb.Object3D(point_cloud)})

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