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        <title><![CDATA[Stories by Rohan Gupta on Medium]]></title>
        <description><![CDATA[Stories by Rohan Gupta on Medium]]></description>
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            <title>Stories by Rohan Gupta on Medium</title>
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            <title><![CDATA[Outliers in Data Engineering — A Quick Overview]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://ai.plainenglish.io/outliers-in-data-engineering-a-quick-overview-7a4bf362bd53?source=rss-f463f1bf80e2------2"><img src="https://cdn-images-1.medium.com/max/2600/0*QKTUGdmBFiOoFmBf" width="6000"></a></p><p class="medium-feed-snippet">Outliers are everywhere.</p><p class="medium-feed-link"><a href="https://ai.plainenglish.io/outliers-in-data-engineering-a-quick-overview-7a4bf362bd53?source=rss-f463f1bf80e2------2">Continue reading on Artificial Intelligence in Plain English »</a></p></div>]]></description>
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            <dc:creator><![CDATA[Rohan Gupta]]></dc:creator>
            <pubDate>Sat, 20 Jun 2020 10:20:19 GMT</pubDate>
            <atom:updated>2020-06-24T13:07:34.827Z</atom:updated>
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            <title><![CDATA[LexNLP — Library For Automated Text Extraction & NER (With]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/data-science/lexnlp-library-for-automated-text-extraction-ner-with-bafd0014a3f8?source=rss-f463f1bf80e2------2"><img src="https://cdn-images-1.medium.com/max/1800/1*Zeol7QEEZm4OfznN7LsFFQ.jpeg" width="1800"></a></p><p class="medium-feed-snippet">Using LexPredict, upcoming advanced library for Named Entity Recognition (NER) to extract names, addresses, dates, etc.</p><p class="medium-feed-link"><a href="https://medium.com/data-science/lexnlp-library-for-automated-text-extraction-ner-with-bafd0014a3f8?source=rss-f463f1bf80e2------2">Continue reading on TDS Archive »</a></p></div>]]></description>
            <link>https://medium.com/data-science/lexnlp-library-for-automated-text-extraction-ner-with-bafd0014a3f8?source=rss-f463f1bf80e2------2</link>
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            <dc:creator><![CDATA[Rohan Gupta]]></dc:creator>
            <pubDate>Fri, 05 Jun 2020 13:47:48 GMT</pubDate>
            <atom:updated>2020-06-05T13:47:48.621Z</atom:updated>
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            <title><![CDATA[NBA All-Star Weekend 2020 —  Predicting Winners with Stats that Matter]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/sportsraid/nba-all-star-weekend-2020-predicting-winners-with-stats-that-matter-24597e192b8?source=rss-f463f1bf80e2------2"><img src="https://cdn-images-1.medium.com/max/2120/1*gamdU8-WUrR7kx_uzsoRMQ.png" width="2120"></a></p><p class="medium-feed-snippet">Stats &amp; Analysis: NBA All-Star Weekend 2020. Who will win?</p><p class="medium-feed-link"><a href="https://medium.com/sportsraid/nba-all-star-weekend-2020-predicting-winners-with-stats-that-matter-24597e192b8?source=rss-f463f1bf80e2------2">Continue reading on SportsRaid »</a></p></div>]]></description>
            <link>https://medium.com/sportsraid/nba-all-star-weekend-2020-predicting-winners-with-stats-that-matter-24597e192b8?source=rss-f463f1bf80e2------2</link>
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            <category><![CDATA[sports]]></category>
            <category><![CDATA[basketball]]></category>
            <category><![CDATA[lebron-james]]></category>
            <category><![CDATA[nba-playoffs]]></category>
            <category><![CDATA[nba]]></category>
            <dc:creator><![CDATA[Rohan Gupta]]></dc:creator>
            <pubDate>Tue, 11 Feb 2020 20:03:45 GMT</pubDate>
            <atom:updated>2020-02-11T21:05:25.942Z</atom:updated>
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            <title><![CDATA[Analyzing Fan Sentiments After NBA Trade Deadline]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/data-science/analyzing-fan-sentiments-after-nba-trade-deadline-1b73f72d0ca2?source=rss-f463f1bf80e2------2"><img src="https://cdn-images-1.medium.com/max/2600/0*LYGC1YUKLRiEmmvI" width="6000"></a></p><p class="medium-feed-snippet">Calculating the overall fan sentiment for teams through Tweets about trades made before the deadline.</p><p class="medium-feed-link"><a href="https://medium.com/data-science/analyzing-fan-sentiments-after-nba-trade-deadline-1b73f72d0ca2?source=rss-f463f1bf80e2------2">Continue reading on TDS Archive »</a></p></div>]]></description>
            <link>https://medium.com/data-science/analyzing-fan-sentiments-after-nba-trade-deadline-1b73f72d0ca2?source=rss-f463f1bf80e2------2</link>
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            <category><![CDATA[sentiment-analysis]]></category>
            <category><![CDATA[analytics]]></category>
            <category><![CDATA[nba]]></category>
            <category><![CDATA[nlp]]></category>
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            <dc:creator><![CDATA[Rohan Gupta]]></dc:creator>
            <pubDate>Sat, 08 Feb 2020 23:32:43 GMT</pubDate>
            <atom:updated>2020-02-10T17:38:40.881Z</atom:updated>
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            <title><![CDATA[8 Clutch Ways to Impute Missing Data]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/data-science/8-clutch-ways-to-impute-missing-data-690481c6cb2b?source=rss-f463f1bf80e2------2"><img src="https://cdn-images-1.medium.com/max/2600/0*vvNaFOC3FRixEFZS" width="2760"></a></p><p class="medium-feed-snippet">A tutorial on how to deal with missing data in any dataset</p><p class="medium-feed-link"><a href="https://medium.com/data-science/8-clutch-ways-to-impute-missing-data-690481c6cb2b?source=rss-f463f1bf80e2------2">Continue reading on TDS Archive »</a></p></div>]]></description>
            <link>https://medium.com/data-science/8-clutch-ways-to-impute-missing-data-690481c6cb2b?source=rss-f463f1bf80e2------2</link>
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            <category><![CDATA[statistics]]></category>
            <category><![CDATA[python]]></category>
            <category><![CDATA[excel]]></category>
            <category><![CDATA[data]]></category>
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            <dc:creator><![CDATA[Rohan Gupta]]></dc:creator>
            <pubDate>Wed, 22 Jan 2020 17:27:16 GMT</pubDate>
            <atom:updated>2020-01-22T22:57:43.305Z</atom:updated>
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            <title><![CDATA[The Fastest and Easiest Way to Forecast Data on Python]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/data-science/the-fastest-and-easiest-way-to-forecast-data-on-python-d7ff29f3add6?source=rss-f463f1bf80e2------2"><img src="https://cdn-images-1.medium.com/max/2600/0*ooaESiGlO1FILkWU" width="5650"></a></p><p class="medium-feed-snippet">Predicting Points by NBA All Stars&#x200A;&#x2014;&#x200A;Who will score the most?</p><p class="medium-feed-link"><a href="https://medium.com/data-science/the-fastest-and-easiest-way-to-forecast-data-on-python-d7ff29f3add6?source=rss-f463f1bf80e2------2">Continue reading on TDS Archive »</a></p></div>]]></description>
            <link>https://medium.com/data-science/the-fastest-and-easiest-way-to-forecast-data-on-python-d7ff29f3add6?source=rss-f463f1bf80e2------2</link>
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            <category><![CDATA[nba]]></category>
            <category><![CDATA[data]]></category>
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            <dc:creator><![CDATA[Rohan Gupta]]></dc:creator>
            <pubDate>Sun, 08 Dec 2019 02:45:54 GMT</pubDate>
            <atom:updated>2019-12-08T06:16:31.301Z</atom:updated>
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            <title><![CDATA[An Introduction to Discretization in Data Science]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/data-science/an-introduction-to-discretization-in-data-science-55ef8c9775a2?source=rss-f463f1bf80e2------2"><img src="https://cdn-images-1.medium.com/max/2600/0*bBSiceGUCQDx9Tpf" width="4325"></a></p><p class="medium-feed-snippet">An Introduction to Discretization Techniques for Data Scientists</p><p class="medium-feed-link"><a href="https://medium.com/data-science/an-introduction-to-discretization-in-data-science-55ef8c9775a2?source=rss-f463f1bf80e2------2">Continue reading on TDS Archive »</a></p></div>]]></description>
            <link>https://medium.com/data-science/an-introduction-to-discretization-in-data-science-55ef8c9775a2?source=rss-f463f1bf80e2------2</link>
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            <category><![CDATA[machine-learning]]></category>
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            <category><![CDATA[python]]></category>
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            <dc:creator><![CDATA[Rohan Gupta]]></dc:creator>
            <pubDate>Fri, 06 Dec 2019 20:36:10 GMT</pubDate>
            <atom:updated>2019-12-06T23:54:41.471Z</atom:updated>
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            <title><![CDATA[Build and Compare 3 Models — NLP Sentiment Prediction]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/data-science/build-and-compare-3-models-nlp-sentiment-prediction-67320979de61?source=rss-f463f1bf80e2------2"><img src="https://cdn-images-1.medium.com/max/1280/1*396DIwqAkvEgYHb-WBggCQ.png" width="1280"></a></p><p class="medium-feed-snippet">Natural Language Processing on Python&#x200A;&#x2014;&#x200A;Beginner Friendly!</p><p class="medium-feed-link"><a href="https://medium.com/data-science/build-and-compare-3-models-nlp-sentiment-prediction-67320979de61?source=rss-f463f1bf80e2------2">Continue reading on TDS Archive »</a></p></div>]]></description>
            <link>https://medium.com/data-science/build-and-compare-3-models-nlp-sentiment-prediction-67320979de61?source=rss-f463f1bf80e2------2</link>
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            <category><![CDATA[machine-learning]]></category>
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            <dc:creator><![CDATA[Rohan Gupta]]></dc:creator>
            <pubDate>Tue, 12 Nov 2019 05:00:16 GMT</pubDate>
            <atom:updated>2019-11-12T05:00:16.544Z</atom:updated>
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            <title><![CDATA[Cleaning Web-Scraped Data with Pandas (Part II)]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/data-science/cleaning-web-scraped-data-with-pandas-part-ii-8520f47cc929?source=rss-f463f1bf80e2------2"><img src="https://cdn-images-1.medium.com/max/2600/0*jU-2JOj62cssuHId" width="4500"></a></p><p class="medium-feed-snippet">How to create meaning out of web-scraped data for Data Analysis and Machine Learning</p><p class="medium-feed-link"><a href="https://medium.com/data-science/cleaning-web-scraped-data-with-pandas-part-ii-8520f47cc929?source=rss-f463f1bf80e2------2">Continue reading on TDS Archive »</a></p></div>]]></description>
            <link>https://medium.com/data-science/cleaning-web-scraped-data-with-pandas-part-ii-8520f47cc929?source=rss-f463f1bf80e2------2</link>
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            <category><![CDATA[pandas]]></category>
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            <dc:creator><![CDATA[Rohan Gupta]]></dc:creator>
            <pubDate>Sat, 09 Nov 2019 20:15:16 GMT</pubDate>
            <atom:updated>2019-11-10T04:14:22.533Z</atom:updated>
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            <title><![CDATA[Cleaning Web-Scraped Data With Pandas and Regex! (Part I)]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/data-science/cleaning-web-scraped-data-with-pandas-and-regex-part-i-a82a177af11b?source=rss-f463f1bf80e2------2"><img src="https://cdn-images-1.medium.com/max/2600/0*OHAh_LpvbNxI2Zku" width="4200"></a></p><p class="medium-feed-snippet">How to create meaning out of web-scraped data for data analysis and machine learning! Part 2&#x200A;&#x2014;&#x200A;coming soon!</p><p class="medium-feed-link"><a href="https://medium.com/data-science/cleaning-web-scraped-data-with-pandas-and-regex-part-i-a82a177af11b?source=rss-f463f1bf80e2------2">Continue reading on TDS Archive »</a></p></div>]]></description>
            <link>https://medium.com/data-science/cleaning-web-scraped-data-with-pandas-and-regex-part-i-a82a177af11b?source=rss-f463f1bf80e2------2</link>
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            <category><![CDATA[data-science]]></category>
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            <dc:creator><![CDATA[Rohan Gupta]]></dc:creator>
            <pubDate>Fri, 01 Nov 2019 20:09:43 GMT</pubDate>
            <atom:updated>2019-11-02T19:11:29.022Z</atom:updated>
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