apricot-submodular-selection-for-data-summarization-scipy-2019-jacob-schreiber.json

{
  "copyright_text": null,
  "description": "Submodular selection can be used to reduce a complex data set down to a representative subset. This subset can then be used to train machine learning models with high efficiency and resulting accuracy. In this talk we will introduce apricot, a Python package for submodular selection, and show examples of its usage.",
  "duration": 1654,
  "language": "eng",
  "recorded": "2019-07-13",
  "related_urls": [
    {
      "label": "Conference schedule",
      "url": "https://www.scipy2019.scipy.org/confschedule"
    }
  ],
  "speakers": [
    "Jacob Schreiber"
  ],
  "tags": [],
  "thumbnail_url": "https://i.ytimg.com/vi/WzhHVYsUGtM/maxresdefault.jpg",
  "title": "apricot: Submodular Selection for Data Summarization",
  "videos": [
    {
      "type": "youtube",
      "url": "https://www.youtube.com/watch?v=WzhHVYsUGtM"
    }
  ]
}