In this video, Weights & Biases Deep Learning Educator Charles Frye demonstrates how to integrate W&B into PyTorch code while avoiding interference from the Mirror Universe and a Kraken attack.
Follow along in Colab: http://wandb.me/pytorch-colab
Check out the Keras version: http://wandb.me/keras-video
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0:00 - What is W&B? How do I add it to my PyTorch code?
3:25 - Installs, imports, and setup
5:49 - Setting hyperparameters and boilerplate
12:03 - Logging metrics and gradients to W&B
15:48 - Reviewing the W&B Dashboard
18:10 - Metadata, system metrics, and model topology in W&B
23:06 - Outro