Time Series Forecasting 2 : ARIMA

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Derek Banas

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Published on November 3, 2020 9:55:10 PM ● Video Link: https://www.youtube.com/watch?v=lBnPUV6FKnA

Duration: 28:46

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In this video I continue teaching you how to predict the future! This time I'm talking about AutoRegressive Integrated Moving Average (ARIMA). ARIMA is the basis for many other models. It focuses on examining differences between values to forecast future values.

I'll start by making sure you completely understand regressions with AutoReg. Along the way I'll teach you how to work with DateTimes, Frequency, Dropping Columns, Cleaning Up Missing Data, and Selecting Data based on Conditions.

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It includes these Additional Videos on Time Series Forecasting that cover :

• Using the Granger Causality Test to Make Stock Market Predictions
• ARIMA Model Parameters
• Resampling
• Auto Correlation Function
• Partial Auto Correlation Function
• Grid Search
• Pyramid ARIMA
• Akaike Information Criterion
• Bayesian Information Criterion

All the Files Used are Here for Free : https://github.com/derekbanas/TimeSeriesAnalysis

More Tutorials on Software Used

Install for Windows : https://youtu.be/a7Ylbn1ikF0
Install for MacOS : https://youtu.be/2JeoNlCcLOM
Algebra : https://youtu.be/B_WCI_A944E
Linear Algebra : https://youtu.be/6GnzRGJsI3Q
Probability in One Video : https://youtu.be/sEte4hXEgJ8
Statistics in One Video : https://youtu.be/tcusIOfI_GM
NumPy in One Video : https://youtu.be/8Y0qQEh7dJg
Pandas in One Video : https://youtu.be/PcvsOaixUh8
Matplotlib in One Video : https://youtu.be/wB9C0Mz9gSo
Seaborn in One Video : https://youtu.be/6GUZXDef2U0
Plotly in One Video : https://youtu.be/GGL6U0k8WYA
Time Series Analysis : https://youtu.be/PpnoNZYce_c

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#Forecasting #DataScience #MachineLearning

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