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        <title><![CDATA[Stories by Minha Hwang on Medium]]></title>
        <description><![CDATA[Stories by Minha Hwang on Medium]]></description>
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            <title>Stories by Minha Hwang on Medium</title>
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            <title><![CDATA[Improving Enterprise AI and Agent When You Can’t See the Data]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/data-science-collective/improving-enterprise-ai-and-agent-when-you-cant-see-the-data-50876924741f?source=rss-4439ff062d93------2"><img src="https://cdn-images-1.medium.com/max/2600/0*8o-Hr1WTMPrr9dQE" width="4069"></a></p><p class="medium-feed-snippet">Four ways to turn eyes-off enterprise data into insights, model updates, evaluations and post-training data, and when each fits chat&#x2026;</p><p class="medium-feed-link"><a href="https://medium.com/data-science-collective/improving-enterprise-ai-and-agent-when-you-cant-see-the-data-50876924741f?source=rss-4439ff062d93------2">Continue reading on Data Science Collective »</a></p></div>]]></description>
            <link>https://medium.com/data-science-collective/improving-enterprise-ai-and-agent-when-you-cant-see-the-data-50876924741f?source=rss-4439ff062d93------2</link>
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            <category><![CDATA[artificial-intelligence]]></category>
            <category><![CDATA[machine-learning]]></category>
            <category><![CDATA[differential-privacy]]></category>
            <category><![CDATA[synthetic-data]]></category>
            <dc:creator><![CDATA[Minha Hwang]]></dc:creator>
            <pubDate>Sun, 01 Nov 2026 17:23:55 GMT</pubDate>
            <atom:updated>2026-11-01T17:44:38.124Z</atom:updated>
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        <item>
            <title><![CDATA[Build and Host a Website in 5 Minutes: From Prompt to Published]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/data-science-collective/build-and-host-a-website-in-5-minutes-from-prompt-to-published-0d4f1a720a50?source=rss-4439ff062d93------2"><img src="https://cdn-images-1.medium.com/max/2600/1*Mtlr1C-8e5NYSca9CyzwXA.jpeg" width="2816"></a></p><p class="medium-feed-snippet">A practical guide to creating your first page with AI and putting it online with Netlify or Vercel.</p><p class="medium-feed-link"><a href="https://medium.com/data-science-collective/build-and-host-a-website-in-5-minutes-from-prompt-to-published-0d4f1a720a50?source=rss-4439ff062d93------2">Continue reading on Data Science Collective »</a></p></div>]]></description>
            <link>https://medium.com/data-science-collective/build-and-host-a-website-in-5-minutes-from-prompt-to-published-0d4f1a720a50?source=rss-4439ff062d93------2</link>
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            <category><![CDATA[artificial-intelligence]]></category>
            <category><![CDATA[website-development]]></category>
            <category><![CDATA[ai-web-design-revolution]]></category>
            <category><![CDATA[ai-agent]]></category>
            <category><![CDATA[web-hosting-services]]></category>
            <dc:creator><![CDATA[Minha Hwang]]></dc:creator>
            <pubDate>Mon, 21 Sep 2026 12:18:11 GMT</pubDate>
            <atom:updated>2026-09-21T13:10:08.723Z</atom:updated>
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        <item>
            <title><![CDATA[Practical Data Science: Promotion Effectiveness and Promotion Planning—Part 3]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/data-science/practical-data-science-promotion-effectiveness-and-promotion-planning-part-3-7207deeacc49?source=rss-4439ff062d93------2"><img src="https://cdn-images-1.medium.com/max/1000/0*y_xvhNJDVfcXIB4N" width="1000"></a></p><p class="medium-feed-snippet">6 Step Process | Step 2&#x200A;&#x2014;&#x200A;Prepare Modeling Dataset (1/2)</p><p class="medium-feed-link"><a href="https://medium.com/data-science/practical-data-science-promotion-effectiveness-and-promotion-planning-part-3-7207deeacc49?source=rss-4439ff062d93------2">Continue reading on TDS Archive »</a></p></div>]]></description>
            <link>https://medium.com/data-science/practical-data-science-promotion-effectiveness-and-promotion-planning-part-3-7207deeacc49?source=rss-4439ff062d93------2</link>
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            <category><![CDATA[promotion]]></category>
            <category><![CDATA[data-science]]></category>
            <category><![CDATA[promotion-effectivenes]]></category>
            <dc:creator><![CDATA[Minha Hwang]]></dc:creator>
            <pubDate>Wed, 14 Dec 2022 03:24:58 GMT</pubDate>
            <atom:updated>2025-01-27T00:39:21.192Z</atom:updated>
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            <title><![CDATA[Practical Data Science: Promotion Effectiveness and Promotion Planning — Part 2]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/data-science/practical-data-science-promotion-effectiveness-and-promotion-planning-part-2-f54e9454a151?source=rss-4439ff062d93------2"><img src="https://cdn-images-1.medium.com/max/1000/0*QrfjvOpRqmqpibIf" width="1000"></a></p><p class="medium-feed-snippet">6 Step Process | Step 1&#x200A;&#x2014;&#x200A;Build Data Foundation</p><p class="medium-feed-link"><a href="https://medium.com/data-science/practical-data-science-promotion-effectiveness-and-promotion-planning-part-2-f54e9454a151?source=rss-4439ff062d93------2">Continue reading on TDS Archive »</a></p></div>]]></description>
            <link>https://medium.com/data-science/practical-data-science-promotion-effectiveness-and-promotion-planning-part-2-f54e9454a151?source=rss-4439ff062d93------2</link>
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            <category><![CDATA[data-engineering]]></category>
            <category><![CDATA[causal-machine-learning]]></category>
            <category><![CDATA[promotion-effectivenes]]></category>
            <category><![CDATA[business]]></category>
            <category><![CDATA[data-science]]></category>
            <dc:creator><![CDATA[Minha Hwang]]></dc:creator>
            <pubDate>Thu, 10 Nov 2022 02:32:10 GMT</pubDate>
            <atom:updated>2025-01-27T00:51:26.818Z</atom:updated>
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        <item>
            <title><![CDATA[Practical Data Science: Promotion Effectiveness and Promotion Planning — Part 1]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/data-science/practical-data-science-promotion-effectiveness-and-promotion-planning-part-1-52f6707a59b9?source=rss-4439ff062d93------2"><img src="https://cdn-images-1.medium.com/max/1000/0*zyB5IqiemO-Kp4Fs" width="1000"></a></p><p class="medium-feed-snippet">Business Problem | Key Concepts | Why should we care?</p><p class="medium-feed-link"><a href="https://medium.com/data-science/practical-data-science-promotion-effectiveness-and-promotion-planning-part-1-52f6707a59b9?source=rss-4439ff062d93------2">Continue reading on TDS Archive »</a></p></div>]]></description>
            <link>https://medium.com/data-science/practical-data-science-promotion-effectiveness-and-promotion-planning-part-1-52f6707a59b9?source=rss-4439ff062d93------2</link>
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            <category><![CDATA[promotion-planning]]></category>
            <category><![CDATA[notes-from-industry]]></category>
            <category><![CDATA[demand-modeling]]></category>
            <category><![CDATA[data-science]]></category>
            <category><![CDATA[causal-inference]]></category>
            <dc:creator><![CDATA[Minha Hwang]]></dc:creator>
            <pubDate>Wed, 05 Oct 2022 04:36:33 GMT</pubDate>
            <atom:updated>2025-01-27T00:33:43.025Z</atom:updated>
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            <title><![CDATA[Cracking Business Case Interviews for Data Scientists — Part 2]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/data-science/cracking-business-case-interviews-for-data-scientists-part-2-c96d9b9a4292?source=rss-4439ff062d93------2"><img src="https://cdn-images-1.medium.com/max/701/1*Df3m-X0DLGGfvH2t4cDXfA.png" width="701"></a></p><p class="medium-feed-snippet">Issue analysis/work plan, Analyses, Synthesis, and Recommendation</p><p class="medium-feed-link"><a href="https://medium.com/data-science/cracking-business-case-interviews-for-data-scientists-part-2-c96d9b9a4292?source=rss-4439ff062d93------2">Continue reading on TDS Archive »</a></p></div>]]></description>
            <link>https://medium.com/data-science/cracking-business-case-interviews-for-data-scientists-part-2-c96d9b9a4292?source=rss-4439ff062d93------2</link>
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            <category><![CDATA[data-scientist-career]]></category>
            <category><![CDATA[business-case-interview]]></category>
            <category><![CDATA[data-science]]></category>
            <category><![CDATA[data-scientist-interview]]></category>
            <category><![CDATA[data-scientist-skills]]></category>
            <dc:creator><![CDATA[Minha Hwang]]></dc:creator>
            <pubDate>Sat, 11 Dec 2021 19:30:30 GMT</pubDate>
            <atom:updated>2022-12-19T01:20:58.210Z</atom:updated>
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        <item>
            <title><![CDATA[Cracking Business Case Interviews for Data Scientists — Step 1) Define a Problem]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/data-science/cracking-business-case-interviews-for-data-scientists-step-1-define-a-problem-6a63f86b9a38?source=rss-4439ff062d93------2"><img src="https://cdn-images-1.medium.com/max/600/0*Vp27L6Ei9ismTy0U.png" width="600"></a></p><p class="medium-feed-snippet">Business case study interview questions are often the most difficult part of the interview process, especially for early data scientists&#x2026;</p><p class="medium-feed-link"><a href="https://medium.com/data-science/cracking-business-case-interviews-for-data-scientists-step-1-define-a-problem-6a63f86b9a38?source=rss-4439ff062d93------2">Continue reading on TDS Archive »</a></p></div>]]></description>
            <link>https://medium.com/data-science/cracking-business-case-interviews-for-data-scientists-step-1-define-a-problem-6a63f86b9a38?source=rss-4439ff062d93------2</link>
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            <category><![CDATA[interview]]></category>
            <category><![CDATA[problem-definition]]></category>
            <category><![CDATA[problem-solving]]></category>
            <category><![CDATA[data-science]]></category>
            <category><![CDATA[data-science-interview]]></category>
            <dc:creator><![CDATA[Minha Hwang]]></dc:creator>
            <pubDate>Mon, 06 Sep 2021 16:04:00 GMT</pubDate>
            <atom:updated>2023-01-28T23:47:33.972Z</atom:updated>
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        <item>
            <title><![CDATA[Prescriptive Data Science: Single Agent/Static Problem — Joint Price Optimization (1/2)]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/codex/prescriptive-data-science-single-agent-static-problem-joint-price-optimization-1-2-7538ccd8b6ed?source=rss-4439ff062d93------2"><img src="https://cdn-images-1.medium.com/max/1064/1*jo2jQQHasvqi7hs9-RqQ1g.png" width="1064"></a></p><p class="medium-feed-snippet">Welcome back. In the previous article, I have described four different types of prescriptive data science problems, which depend on two&#x2026;</p><p class="medium-feed-link"><a href="https://medium.com/codex/prescriptive-data-science-single-agent-static-problem-joint-price-optimization-1-2-7538ccd8b6ed?source=rss-4439ff062d93------2">Continue reading on CodeX »</a></p></div>]]></description>
            <link>https://medium.com/codex/prescriptive-data-science-single-agent-static-problem-joint-price-optimization-1-2-7538ccd8b6ed?source=rss-4439ff062d93------2</link>
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            <category><![CDATA[ai]]></category>
            <category><![CDATA[pricing]]></category>
            <category><![CDATA[data-science]]></category>
            <category><![CDATA[optimization]]></category>
            <category><![CDATA[prescriptive-analytics]]></category>
            <dc:creator><![CDATA[Minha Hwang]]></dc:creator>
            <pubDate>Sun, 29 Aug 2021 18:21:00 GMT</pubDate>
            <atom:updated>2021-09-04T19:57:40.305Z</atom:updated>
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            <title><![CDATA[Prescriptive Data Science 101: Types of Problems]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/data-science/prescriptive-data-science-101-types-of-problems-and-methods-for-a-single-agent-case-e80cf879ccb6?source=rss-4439ff062d93------2"><img src="https://cdn-images-1.medium.com/max/700/0*Ly0o_DiwFBe812Ox" width="700"></a></p><p class="medium-feed-snippet">Key dimensions: single/multiple agents | static/dynamic problems</p><p class="medium-feed-link"><a href="https://medium.com/data-science/prescriptive-data-science-101-types-of-problems-and-methods-for-a-single-agent-case-e80cf879ccb6?source=rss-4439ff062d93------2">Continue reading on TDS Archive »</a></p></div>]]></description>
            <link>https://medium.com/data-science/prescriptive-data-science-101-types-of-problems-and-methods-for-a-single-agent-case-e80cf879ccb6?source=rss-4439ff062d93------2</link>
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            <category><![CDATA[reinforcement-learning]]></category>
            <category><![CDATA[tech]]></category>
            <category><![CDATA[prescriptive-analytics]]></category>
            <category><![CDATA[statistics]]></category>
            <category><![CDATA[artificial-intelligence]]></category>
            <dc:creator><![CDATA[Minha Hwang]]></dc:creator>
            <pubDate>Fri, 06 Aug 2021 02:49:52 GMT</pubDate>
            <atom:updated>2022-11-08T03:04:39.678Z</atom:updated>
        </item>
        <item>
            <title><![CDATA[Prescriptive Data Science: Beyond Predictive Data Science]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/data-science/prescriptive-data-science-beyond-predictive-data-science-51bde1900c1e?source=rss-4439ff062d93------2"><img src="https://cdn-images-1.medium.com/max/2600/0*y8F_QYW5Yxh8lFkM" width="6144"></a></p><p class="medium-feed-snippet">(1) Descriptive, predictive, and prescriptive data science; (2) Required skillsets and key components in prescriptive data science</p><p class="medium-feed-link"><a href="https://medium.com/data-science/prescriptive-data-science-beyond-predictive-data-science-51bde1900c1e?source=rss-4439ff062d93------2">Continue reading on TDS Archive »</a></p></div>]]></description>
            <link>https://medium.com/data-science/prescriptive-data-science-beyond-predictive-data-science-51bde1900c1e?source=rss-4439ff062d93------2</link>
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            <category><![CDATA[data-science]]></category>
            <category><![CDATA[machine-learning]]></category>
            <category><![CDATA[optimization]]></category>
            <category><![CDATA[prescriptive-analytics]]></category>
            <category><![CDATA[data-scientist-skills]]></category>
            <dc:creator><![CDATA[Minha Hwang]]></dc:creator>
            <pubDate>Sun, 18 Jul 2021 20:51:53 GMT</pubDate>
            <atom:updated>2022-11-08T03:05:16.622Z</atom:updated>
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