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Autoregression (AR)
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Classroom Contents
Deep Learning Your Broadband Network at Home
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- 1 Intro
- 2 Outline
- 3 Home Network
- 4 Anomaly Detection (Naive approach in 2015)
- 5 Problem definition
- 6 Types of anomalies in time series
- 7 Logging Data
- 8 Data preparation
- 9 Handling time series
- 10 Components of Time series data
- 11 Seasonal Trend Decomposition
- 12 Rolling Forecast
- 13 Anomaly Detection (Basic approach)
- 14 Anomaly Detection (Naive approach)
- 15 Stationary Series Criterion
- 16 Test Stationarity
- 17 Autoregression (AR)
- 18 Moving Average (MA)
- 19 Identification of ARIMA (easy case)
- 20 Identification of ARIMA (complicated)
- 21 Anomaly Detection (Parameter Estimation)
- 22 Anomaly Detection Multivariate Gaussian Distribution
- 23 Anomaly Detection (Multivariate Gaussian)
- 24 Long Short-Term Memory
- 25 Summary
- 26 Contacts
- 27 Patterns in time series
