time-series-analysis-with-seasonal-data.json

{
  "copyright_text": null,
  "description": "Case Study in Travel Business\n\nFor time series analysis, everyone\u2019s talking about ARIMA or\nHolt-Winters. But there\u2019s other models which could also break down a\nseasonal series into trend, seasonality and noise. We will use an open\nsource Python library called Seasonal to analyse B2B worldwide travel\ndata.",
  "duration": 1458,
  "language": "eng",
  "recorded": "2018-09-18",
  "related_urls": [
    {
      "label": "Conference schedule",
      "url": "http://2018.pyconuk.org/schedule/"
    }
  ],
  "speakers": [
    "Cheuk Ting Ho"
  ],
  "tags": [],
  "thumbnail_url": "https://i.ytimg.com/vi/B3ACmn8bsgo/maxresdefault.jpg",
  "title": "Time Series Analysis with Seasonal Data",
  "videos": [
    {
      "type": "youtube",
      "url": "https://www.youtube.com/watch?v=B3ACmn8bsgo"
    }
  ]
}