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https://github.com/charlesfrye/docs-box

A sandbox for docs
https://github.com/charlesfrye/docs-box

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A sandbox for docs

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README

        

---
description: 'Track machine learning experiments, visualize metrics, and share results'
---

# Weights & Biases

Weights & Biases helps you keep track of your machine learning projects. Use our tool to log hyperparameters and output metrics from your runs, then visualize and compare results and quickly share findings with your colleagues.

![](.gitbook/assets/workflow-june-2020-v1.png)

Our tools work with your machine learning infrastructure: AWS, GCP, Kubernetes, Azure, and on-prem machines.

## Tools

1. [**Dashboard**](app/): Track experiments, visualize results
2. [**Reports**](reports.md): Save and share reproducible findings
3. [**Sweeps**](sweeps/): Optimize models with hyperparameter tuning
4. [**Artifacts**](artifacts/): Dataset and model versioning, pipeline tracking

{% embed url="https://youtu.be/gnD8BFuyVUA" caption="" %}

## Getting Started

Easily add our Python library `wandb` to your machine learning script.

* [Quickstart](quickstart.md)
* [Keras integration](integrations/keras.md)
* [PyTorch integration](integrations/pytorch.md)
* [TensorFlow integration](integrations/tensorflow.md)
* [Jupyter notebook integration](integrations/jupyter.md)

Here's a sample screenshot from a [Species Identification project](https://app.wandb.ai/stacey/curr_learn/reports?view=stacey%2FSpecies%20Identification) in W&B.

![](.gitbook/assets/screen-shot-2020-08-07-at-1.16.16-pm.png)

## Examples

If you're interested in example projects, we have a few resources:

* [App Gallery](https://app.wandb.ai/gallery): A gallery of featured reports in our web app
* [Example Projects](https://github.com/charlesfrye/docs-box/tree/62d9038f970341b063901adb4364344e016c610f/examples.md): Code and projects in GitHub and Colab