Create a framework for a dynamic demand forecasting model using exponential smoothing, incorporating historical sales data, seasonality, and trend analysis.
Task: generate a summary of a video. Input: [video title], [video transcript], [length of summary: e.g., 100 words, 200 words] Instruction: summarize the video transcript, focusing on the main topics and key takeaways. The summary should be concise and informative, providing a clear overview of the video's content. Adhere to the specified length constraint.
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Generate a detailed, multi-factor demand forecasting model for a specific product or SKU, considering historical data, seasonality, trends, and external variables.
Generate a runnable Python script for advanced demand forecasting models like ARIMA or Prophet, incorporating historical sales data and external influencing factors to optimize inventory planning.
Generate a simple moving average forecast for a product based on historical sales data.
