Air Passenger Data Analysis | Time Series Forecasting | SARIMAX | Python

⭐️ Content Description ⭐️
In this video, I have explained about time series forecasting using ARIMA with the help of air passenger dataset. The process consists of EDA to find the parameters of ARIMA for performing the forecast of 24 months in future using the historical data available.
GitHub Code Repo: http://bit.ly/mlcoderepo
Dataset link: https://www.kaggle.com/datasets/rakannimer/air-passengers
Text-based Tutorial: https://www.hackersrealm.net/post/air-passenger-time-series-forecasting

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🕒 Timeline
00:00 Introduction to Time Series Forecasting
00:36 Import Modules
01:55 Load the Air Passenger Dataset
03:03 Exploratory Data Analysis (Seasonal Decomposition)
12:53 Find p, d, q parameters using ACF & PACF
26:56 Train ARIMA Model
29:16 Forecast Future Steps
38:51 Find P, D, Q parameters for Seasonal Order

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Видео Air Passenger Data Analysis | Time Series Forecasting | SARIMAX | Python канала Hackers Realm
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