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<title>RSS feed - SEOClerks</title>
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<language>en-us</language> <pubDate>Wed, 22 Apr 2026 00:56:00 +0000</pubDate>
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  <title><![CDATA[Built an fascinating, well designed email template for $15]]></title>
  <link><![CDATA[https://www.seoclerk.com/email-newsletters/1206490/Built-an-fascinating-well-designed-email-template]]></link>
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  <description>
    <![CDATA[We offer excellent design, development and marketing services.

Professional graphic designing and web development with 8+ years of experience specialize in designing mailer, flyer, infographics, logos and social media designs

Web page, UX/UI, app design

Why Should You Consider this service?

 Completely Responsive on Desktop as well as Mobile Devices. All Email Templates are Tested on various Platforms to ensure functionality Latest Trends in all Designs Quality Assurance Friendly Customer Support <br><br>by: <a href="https://www.seoclerk.com/user/Rajark159">Rajark159</a><br />Created: --<br>Category: <a href='https://www.seoclerk.com/categories/email-newsletters'>Email & Newsletters</a><br>Viewed: 1505<br/><br/><br /><hr>    ]]>
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  <dc:creator>Rajark159</dc:creator>
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<item>
  <title><![CDATA[Recommendation System using python for $15]]></title>
  <link><![CDATA[https://www.seoclerk.com/Programming/1204450/Recommendation-System-using-python]]></link>
  <guid><![CDATA[https://www.seoclerk.com/Programming/1204450/Recommendation-System-using-python]]></guid>
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    <![CDATA[Recommendation engines are a subclass of machine learning which generally deal with ranking or rating products / users. Loosely defined, a recommender system is a system which predicts ratings a user might give to a specific item. These predictions will then be ranked and returned back to the user.

Types of Recommendation system:

 User based filtering - Building a model from user's past behavior as well as similar decisions made by other users. This model is used to predict items that user may have interest in. Content based filtering - Utilizes a series of discrete characteristics of an item in order to recommend additional item with similar properties to the user. <br><br>by: <a href="https://www.seoclerk.com/user/Rajark159">Rajark159</a><br />Created: --<br>Category: <a href='https://www.seoclerk.com/categories/Programming'>Programming</a><br>Viewed: 1971<br/><br/><br /><hr>    ]]>
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  <dc:creator>Rajark159</dc:creator>
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