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What is principal component analysis in AI?The Complete Developer Course Part#14. The Complete Artificial Intelegence Developer Course 2022 [Videos].

Principal Component Analysis (PCA) is a powerful statistical technique for variable reduction, It used when variables are highly correlated. ... PCA incorporated with AI techniques to improve performance of many applications like image processing, pattern recognition, classification and anomaly detection.

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Artificial Intelegence / Youtube

What is principal component analysis in AI?The Complete Developer Course Part#14

Principal Component Analysis (PCA) is a powerful statistical technique for variable reduction, It used when variables are highly correlated. ... PCA incorporated with AI techniques to improve performance of many applications like image processing, pattern recognition, classification and anomaly detection.
3-jan-2022 /11 /94

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What is the difference between Arima and exponential smoothing?The Complete Developer Course Part#18

Exponential smoothings methods are appropriate for non-stationary data (ie data with a trend and seasonal data). ARIMA models should be used on stationary data only. One should therefore remove the trend of the data (via deflating or logging), and then look at the differenced series.
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rolling() function is a very useful function. It Provides rolling window calculations over the underlying data in the given Series object. Syntax: Series.rolling(window, min_periods=None, center=False, win_type=None, on=None, axis=0, closed=None)
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