📚 node [[data_augmentation|data augmentation]]
Welcome! Nobody has contributed anything to 'data_augmentation|data augmentation' yet. You can:
  • Write something in the document below!
    • There is at least one public document in every node in the Agora. Whatever you write in it will be integrated and made available for the next visitor to read and edit.
  • Write to the Agora from social media.
    • If you follow Agora bot on a supported platform and include the wikilink [[data_augmentation|data augmentation]] in a post, the Agora will link it here and optionally integrate your writing.
  • Sign up as a full Agora user.
    • As a full user you will be able to contribute your personal notes and resources directly to this knowledge commons. Some setup required :)
⥅ related node [[data_augmentation]]
⥅ node [[data_augmentation]] pulled by Agora
📓 garden/KGBicheno/Artificial Intelligence/Introduction to AI/Week 3 - Introduction/Definitions/Data_Augmentation.md by @KGBicheno

data augmentation

Go back to the [[AI Glossary]]

#image

Artificially boosting the range and number of training examples by transforming existing examples to create additional examples. For example, suppose images are one of your features, but your dataset doesn't contain enough image examples for the model to learn useful associations. Ideally, you'd add enough labeled images to your dataset to enable your model to train properly. If that's not possible, data augmentation can rotate, stretch, and reflect each image to produce many variants of the original picture, possibly yielding enough labeled data to enable excellent training.
📖 stoas
⥱ context
← back
ai glossary

↑ pushing here
(none)

↓ pulling this
(none)
→ forward
(none)
🔎 full text search for 'data_augmentation|data augmentation'