Домашнее задание к уроку 27 в учебнике

An end-to-end predictive analytics pipeline built in R using 30-minute interval data from AEMO. This project utilizes a Fourier-expanded ARIMA model to capture extreme intraday solar generation volatility. By modeling these daily cycles, the pipeline drops the baseline forecasting error (MAPE) from 35.8% down to 4.73%. Includes an embedded interactive Tableau dashboard tracking the 48-hour forward projections.

Dataset: https://www.kaggle.com/datasets/dansbecker/nba-shot-logs