Time Series Analysis - When Good Enough is Good Enough
summary
Practical approaches to time series analysis that prioritize simplicity and adequacy over perfect models, illustrating techniques and decision-making when 'good enough' forecasting or analysis suffices. Emphasis is on applied methods and trade-offs rather than complex theoretical models, with examples relevant to common Python-based workflows at PyCon Israel 2017.
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chapters (4)
- 0:00Start
- 5:23Time series is a tough problem
- 10:10autoregressive integrated moving average
- 17:23Time series analysis when "good enough" is good enough
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