Posts tagged small data

With transfer learning, we can take a pretrained model, which was trained on a large readily available dataset (trained on a completely different task, with the same input but different output). Then try to find layers which output reusable features. We use the output of that layer as input features to train a much smaller network that requires a smaller number of parameters. This smaller network only needs to learn the relations for your specific problem having already learnt about patterns in the data from the pretrained model. This way a model trained to detect Cats can be reused to Reproduce the work of Van Gogh

via https://medium.com/nanonets/nanonets-how-to-use-deep-learning-when-you-have-limited-data-f68c0b512cab

There is a lot of talk about “big data” at the moment. For example, this is Big Data Week, which will see events about big data in dozens of cities around the world. But the discussions around big data miss a much bigger and more important picture: the real opportunity is not big data, but small data. Not centralized “big iron”, but decentralized data wrangling. Not “one ring to rule them all” but “small pieces loosely joined”.

http://blog.okfn.org/2013/04/22/forget-big-data-small-data-is-the-real-revolution/

The archival record … is best understood as a sliver of a sliver of a sliver of a window into process. It is a fragile thing, an enchanted thing, defined not by its connections to “reality,” but by its open-ended layerings of construction and reconstruction. Far from constituting the solid structure around which imagination can play, it is itself the stuff of imagination.

http://inkdroid.org/journal/2013/11/26/the-web-as-a-preservation-medium/