1. Model Validation (all models) - rolling forecast sales based on historical data (+ external features) for validating result
2. Forecast Production (selected models) - forecast sales based on historical data (+ external features) and perform model selection based on historical forecast

• Single Exponential Smoothing (Simple Smoothing)
• Double Exponential Smoothing (Holt’s Method)
• Triple Exponential Smoothing (Holt-Winters’ Method)
• Simple Moving Average
• Weighted Moving Average
• Exponential Moving Average
• ARIMA (Autoregressive Integrated Moving Average)
• ARIMAX (Autoregressive Integrated Moving Average with Explanatory Variable)
• Prophet by Facebook
• Linear Regression
• Random Forest
• XGBoost
• LSTM (Long Short-Term Memory)

apikey: [AUTH_KEY]

{
	"run": "[validate/forecast]",
	"path": "[PATH_TO_RUNNING_CONFIGURATION_FILE]"
}

1. Build Container

git clone https://github.com/ssiwapol/time-series-forecasting.git
cd time-series-forecasting
docker build -t [IMAGE_NAME] .

2. Prepare config.yaml and Cloud Authentication File (other directory)

config.yaml

PLATFORM: [local/gcp]
APIKEY: [API_KEY]
DEBUG: [TRUE/FALSE]
PORT: [PORT]
TIMEZONE: [TIMEZONE]
LOG_TAG: [LOG_TAG_IN_CLOUD]
CLOUD_AUTH: [CLOUD_AUTH_FILE]

3. Run Container

docker run --name [CONTAINER_NAME] -v $(pwd):/app/tmp -d -p [PORT]:5000 [IMAGE_NAME]