Module 12 Python Implementation ARIMA Model | Multivariate Regression and Time Series | Data Science

Welcome to Module 12 of our course, where we dive into the practical implementation of ARIMA models using Python. In this video, we will walk you through the step-by-step process of importing necessary libraries, loading a dataset, conducting ETS decomposition, analyzing parameters for the ARIMA model, and splitting the data into training and testing sets.

We'll show you how to fit an ARIMA model to your time series data and make predictions against the test set. We'll also demonstrate how to use your ARIMA model for forecasting. If you're interested in time series analysis and prediction using Python, this module is a must-watch.

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