W&B Tables and Ray
summary
Shows W&B Tables and Artifacts used with Ray to log example-level results: a 3-class Inception model evaluates a rock–paper–scissors dataset, producing a table of images, top scores and predictions, with 4,000 train / 500 val / 500 test splits and observed misclass counts like 21 and 27 for certain confusions. Tables store images once, support computed columns (IOU >= 0.5), side-by-side model comparisons, distributed logging via Ray and collaborative artifacts, and HTML artifact views from spaCy + scattertext.
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chapters (12)
- 0:00Start
- 1:20Experiment Tracking Tools
- 1:49Artifacts
- 2:48Production Monitoring
- 4:32Install the Weights and Biases Library
- 13:51Confusion Matrix
- 14:38Collaborative Artifacts
- 17:21Interactive Tables
- 20:14A Computed Column
- 20:29Computed Column
- 21:40Compare Two Models
- 22:46Nlp Example Using Spacey
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