forecasting-with-the-kalman-filter.json

{
  "copyright_text": "Standard YouTube License",
  "description": "PyData Chicago 2016\n\nGithub: https://github.com/mikemull/Notebooks/blob/master/Kalman-Slides-PyDataChicago2016.ipynb\n\nThe Kalman filter is a popular tool in control theory and time-series analysis, but it can be a little hard to grasp. This talk will serve as in introduction to the concept, using an example of forecasting an economic indicator with tools from the statsmodels library.",
  "duration": 2329,
  "language": "eng",
  "recorded": "2016-08-27",
  "related_urls": [
    "https://github.com/mikemull/Notebooks/blob/master/Kalman-Slides-PyDataChicago2016.ipynb",
    "http://pydata.org/chicago2016/schedule/presentation/22/"
  ],
  "speakers": [
    "Mike Mull"
  ],
  "tags": [
    "Kalman Filter"
  ],
  "thumbnail_url": "https://i.ytimg.com/vi/GmSXhmbv5Zg/maxresdefault.jpg",
  "title": "Forecasting with the Kalman Filter",
  "videos": [
    {
      "type": "youtube",
      "url": "https://www.youtube.com/watch?v=GmSXhmbv5Zg"
    }
  ]
}