Here is the list of the videos and the corresponding book chapter.
Intro
- Business Analytics Using Forecasting (Intro) (3:36)
Chapter 1
- Intro: Forecasting language & notation (7:54)
- Intro: Forecasting future values vs. past values (8:20)
- Interviews: Interview with YouBike spokesperson about forecasting (4:43)
- Interviews: Interview with NTHU VP for General Affairs about forecasting (5:34)
- Forecasting electricity load: Interview with Prof. Tao Hong (5:46)
- Interviews: Interview with NTHU library Collection Division Head about forecasting (4:47)
- Interview with manager at Smile Cafe (at NTHU) (1:40)
Chapter 2
- Exploring time series using visualization (with Tableau) (10:39)
Chapter 3
- Performance 1: Data partitioning for time series (7:11)
- Performance 2: Using software for partitioning time series (3:38)
- Performance 3: Naive forecasts (4:36)
- Performance 4: Predictive metrics & charts (20:32)
Chapter 5
- Smoothing 1: Moving Average for visualization (5:01)
- Smoothing 2: Moving Average for forecasting (11:09)
- Smoothing 3: Differencing (4:34)
- Smoothing 4: Simple exponential smoothing (SES) (12:21)
- Smoothing 5: Holt's exponential smoothing (11:59)
- Smoothing 6: Winter's exponential smoothing (9:18)
- Smoothing 7: Automation and prediction intervals (3:25)
Chapter 6
- Regression 1: Regression for forecasting (4:48)
- Regression 2: Linear trend model (7:04)
- Regression 3: Other trend models (8:16)
- Regression 4: Model for capturing seasonality (8:01)
Chapter 7
- Autocorrelation (6:57)
- Autoregressive model for forecast errors (11:14)
- ARIMA Models (12:02)
- Regression: Including external information (Part A) (8:38)
- Regression: Including external information (Part B) (13:36)
- Forecasting and big data: Interview with Prof. Rob Hyndman (7:27)
- Concluding the journey (5:55)
Chapter 8
- Binary Forecasts: Part A (9:35)
- Binary Forecasts: Part B (7:01)
- Forecasting with Logistic Regression: Part A (3:01)
- Forecasting with Logistic Regression: Part B (9:16)
Chapter 9
- Forecasting with Neural Networks: Part A (11:48)
- Forecasting with Neural Networks: Part B (10:33)
- Forecasting with Neural Networks: Part C (7:15)
Chapter 10
- Communication and Maintenance (13:30)
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