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        <title>Forecasting - Tag - Steven Purcell</title>
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        <description>Forecasting - Tag - Steven Purcell</description>
        <generator>Hugo -- gohugo.io</generator><language>en</language><managingEditor>steven.ray.purcell@gmail.com (Steven Purcell)</managingEditor>
            <webMaster>steven.ray.purcell@gmail.com (Steven Purcell)</webMaster><lastBuildDate>Wed, 13 Sep 2023 09:42:06 -0400</lastBuildDate><atom:link href="http://stevenpurcell.ninja/tags/forecasting/" rel="self" type="application/rss+xml" /><item>
    <title>Traditional Methods vs AI Methods in Forecasting</title>
    <link>http://stevenpurcell.ninja/posts/tradtional_forecasting_vs_ai/</link>
    <pubDate>Wed, 13 Sep 2023 09:42:06 -0400</pubDate>
    <author>Steven Purcell</author>
    <guid>http://stevenpurcell.ninja/posts/tradtional_forecasting_vs_ai/</guid>
    <description><![CDATA[Traditional Methods vs AI Methods in Forecasting: When Simplicity Outperforms Complexity Forecasting remains an indispensable tool for businesses to make informed decisions about future trends, demands, and opportunities. Accurate forecasts can lead to better resource allocation, inventory management, and strategic planning. When it comes to forecasting, data scientists have many tools at their disposal, ranging from traditional and time-tested methods to advanced artificial intelligence (AI) techniques. While AI methods have gained significant attention in recent years, traditional forecasting methods like Moving Average, Exponential Moving Average, and Linear Regression Forecasting still hold their ground in many real-world scenarios.]]></description>
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