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    <channel>
        <title><![CDATA[Stories by Pelin Okutan on Medium]]></title>
        <description><![CDATA[Stories by Pelin Okutan on Medium]]></description>
        <link>https://medium.com/@pelinokutan?source=rss-334463d4b90d------2</link>
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            <title>Stories by Pelin Okutan on Medium</title>
            <link>https://medium.com/@pelinokutan?source=rss-334463d4b90d------2</link>
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        <lastBuildDate>Mon, 25 May 2026 22:13:24 GMT</lastBuildDate>
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        <item>
            <title><![CDATA[Feature Engineering: Potential of Latitude and Longitude]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/@pelinokutan/feature-engineering-potential-of-latitude-and-longitude-16f87c6a5631?source=rss-334463d4b90d------2"><img src="https://cdn-images-1.medium.com/max/1200/0*EQeMd3DUn3ryGa_Q.png" width="1200"></a></p><p class="medium-feed-snippet">Geospatial data is everywhere, from the maps powering ride-hailing services to the recommendation systems suggesting your next vacation&#x2026;</p><p class="medium-feed-link"><a href="https://medium.com/@pelinokutan/feature-engineering-potential-of-latitude-and-longitude-16f87c6a5631?source=rss-334463d4b90d------2">Continue reading on Medium »</a></p></div>]]></description>
            <link>https://medium.com/@pelinokutan/feature-engineering-potential-of-latitude-and-longitude-16f87c6a5631?source=rss-334463d4b90d------2</link>
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            <category><![CDATA[geospatial-data]]></category>
            <category><![CDATA[latitude-and-longitude]]></category>
            <category><![CDATA[machine-learning-models]]></category>
            <category><![CDATA[python]]></category>
            <category><![CDATA[feature-engineering]]></category>
            <dc:creator><![CDATA[Pelin Okutan]]></dc:creator>
            <pubDate>Sun, 15 Dec 2024 01:28:22 GMT</pubDate>
            <atom:updated>2024-12-15T01:28:22.244Z</atom:updated>
        </item>
        <item>
            <title><![CDATA[How Monte Carlo Simulation Enhances Forecasting Accuracy in Uncertain Markets]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/@pelinokutan/how-monte-carlo-simulation-enhances-forecasting-accuracy-in-uncertain-markets-88332b84240e?source=rss-334463d4b90d------2"><img src="https://cdn-images-1.medium.com/max/1500/0*fZxLkoqDaLM2Dbjh.jpg" width="1500"></a></p><p class="medium-feed-snippet">Forecasting is a key part of decision-making across industries, from finance to supply chain management. But predicting the future can be&#x2026;</p><p class="medium-feed-link"><a href="https://medium.com/@pelinokutan/how-monte-carlo-simulation-enhances-forecasting-accuracy-in-uncertain-markets-88332b84240e?source=rss-334463d4b90d------2">Continue reading on Medium »</a></p></div>]]></description>
            <link>https://medium.com/@pelinokutan/how-monte-carlo-simulation-enhances-forecasting-accuracy-in-uncertain-markets-88332b84240e?source=rss-334463d4b90d------2</link>
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            <category><![CDATA[forecasting-accuracy]]></category>
            <category><![CDATA[demand-prediction]]></category>
            <category><![CDATA[monte-carlo-simulation]]></category>
            <category><![CDATA[scenario-analysis]]></category>
            <category><![CDATA[probability-distributions]]></category>
            <dc:creator><![CDATA[Pelin Okutan]]></dc:creator>
            <pubDate>Sun, 27 Oct 2024 15:14:01 GMT</pubDate>
            <atom:updated>2024-10-27T15:14:01.271Z</atom:updated>
        </item>
        <item>
            <title><![CDATA[Modern Route Optimization with Python]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/@pelinokutan/modern-route-optimization-with-python-dc33f9239057?source=rss-334463d4b90d------2"><img src="https://cdn-images-1.medium.com/max/765/0*YdaZxTWGIT62Qzqi.jpg" width="765"></a></p><p class="medium-feed-snippet">Modern Route Optimization with Python: Shortest Path, Traveling Salesman Problem, Vehicle Routing Problem, Plotting Maps and Animations</p><p class="medium-feed-link"><a href="https://medium.com/@pelinokutan/modern-route-optimization-with-python-dc33f9239057?source=rss-334463d4b90d------2">Continue reading on Medium »</a></p></div>]]></description>
            <link>https://medium.com/@pelinokutan/modern-route-optimization-with-python-dc33f9239057?source=rss-334463d4b90d------2</link>
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            <category><![CDATA[route-optimization]]></category>
            <category><![CDATA[data-visualization-python]]></category>
            <category><![CDATA[vehicle-routing]]></category>
            <category><![CDATA[shortest-path-algorithm]]></category>
            <category><![CDATA[traveling-salesman]]></category>
            <dc:creator><![CDATA[Pelin Okutan]]></dc:creator>
            <pubDate>Tue, 01 Oct 2024 09:52:08 GMT</pubDate>
            <atom:updated>2024-10-01T09:52:08.911Z</atom:updated>
        </item>
        <item>
            <title><![CDATA[Predict Your Customer Churn Patterns: Logistic Regression]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/@pelinokutan/predict-your-customer-churn-patterns-logistic-regression-31734398b689?source=rss-334463d4b90d------2"><img src="https://cdn-images-1.medium.com/max/600/0*nzC2flkYvag8Feog.png" width="600"></a></p><p class="medium-feed-snippet">Understanding customer behavior is crucial for any business aiming to thrive. One of the key metrics that can significantly impact a&#x2026;</p><p class="medium-feed-link"><a href="https://medium.com/@pelinokutan/predict-your-customer-churn-patterns-logistic-regression-31734398b689?source=rss-334463d4b90d------2">Continue reading on Medium »</a></p></div>]]></description>
            <link>https://medium.com/@pelinokutan/predict-your-customer-churn-patterns-logistic-regression-31734398b689?source=rss-334463d4b90d------2</link>
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            <category><![CDATA[machine-learning]]></category>
            <category><![CDATA[binary-classification]]></category>
            <category><![CDATA[customer-churn-prediction]]></category>
            <category><![CDATA[data-analysis-with-python]]></category>
            <category><![CDATA[logistic-regression]]></category>
            <dc:creator><![CDATA[Pelin Okutan]]></dc:creator>
            <pubDate>Fri, 20 Sep 2024 09:29:32 GMT</pubDate>
            <atom:updated>2024-09-20T09:34:10.562Z</atom:updated>
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        <item>
            <title><![CDATA[Dynamic Pricing with Reinforcement Learning from Scratch: Q-Learning]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/@pelinokutan/dynamic-pricing-with-reinforcement-learning-from-scratch-q-learning-6a2aa4f5acdb?source=rss-334463d4b90d------2"><img src="https://cdn-images-1.medium.com/max/600/0*ALO3zTie9XK6-ngi.png" width="600"></a></p><p class="medium-feed-snippet">Pricing decisions can make or break a company. Dynamic pricing allows companies to adjust prices in real-time based on demand, supply, and&#x2026;</p><p class="medium-feed-link"><a href="https://medium.com/@pelinokutan/dynamic-pricing-with-reinforcement-learning-from-scratch-q-learning-6a2aa4f5acdb?source=rss-334463d4b90d------2">Continue reading on Medium »</a></p></div>]]></description>
            <link>https://medium.com/@pelinokutan/dynamic-pricing-with-reinforcement-learning-from-scratch-q-learning-6a2aa4f5acdb?source=rss-334463d4b90d------2</link>
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            <category><![CDATA[reinforcement-learning]]></category>
            <category><![CDATA[q-learning-algorithm]]></category>
            <category><![CDATA[price-adjustments]]></category>
            <category><![CDATA[dynamic-pricing]]></category>
            <category><![CDATA[revenue-optimization]]></category>
            <dc:creator><![CDATA[Pelin Okutan]]></dc:creator>
            <pubDate>Fri, 13 Sep 2024 12:47:20 GMT</pubDate>
            <atom:updated>2024-09-20T09:37:54.392Z</atom:updated>
        </item>
        <item>
            <title><![CDATA[A Comprehensive Guide to ESG Standards and Frameworks]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/@pelinokutan/a-comprehensive-guide-to-esg-standards-and-frameworks-be1d4178ddda?source=rss-334463d4b90d------2"><img src="https://cdn-images-1.medium.com/max/600/0*6pYzzgiFhSwB7z1J" width="600"></a></p><p class="medium-feed-snippet">Environmental, Social, and Governance (ESG) factors have risen to the forefront of corporate strategies, financial markets, and investment&#x2026;</p><p class="medium-feed-link"><a href="https://medium.com/@pelinokutan/a-comprehensive-guide-to-esg-standards-and-frameworks-be1d4178ddda?source=rss-334463d4b90d------2">Continue reading on Medium »</a></p></div>]]></description>
            <link>https://medium.com/@pelinokutan/a-comprehensive-guide-to-esg-standards-and-frameworks-be1d4178ddda?source=rss-334463d4b90d------2</link>
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            <category><![CDATA[esg-framework]]></category>
            <category><![CDATA[climate-risk-disclosure]]></category>
            <category><![CDATA[sustainability-reporting]]></category>
            <category><![CDATA[corporate-responsibility]]></category>
            <category><![CDATA[financial-materiality]]></category>
            <dc:creator><![CDATA[Pelin Okutan]]></dc:creator>
            <pubDate>Sat, 07 Sep 2024 15:10:03 GMT</pubDate>
            <atom:updated>2024-09-07T15:10:03.889Z</atom:updated>
        </item>
        <item>
            <title><![CDATA[Time Series Forecasting with Python: Practical Implementations of SARIMAX, RNN, LSTM, Prophet, and…]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/@pelinokutan/time-series-forecasting-with-python-practical-implementations-of-sarimax-rnn-lstm-prophet-and-aa0a02e70fa4?source=rss-334463d4b90d------2"><img src="https://cdn-images-1.medium.com/max/1212/1*sZqwSVBfNOAKqW0GmHXIrw.png" width="1212"></a></p><p class="medium-feed-snippet">In my previous article, Time Series Forecasting: A Comparative Analysis of SARIMAX, RNN, LSTM, Prophet, and Transformer Models, I explored&#x2026;</p><p class="medium-feed-link"><a href="https://medium.com/@pelinokutan/time-series-forecasting-with-python-practical-implementations-of-sarimax-rnn-lstm-prophet-and-aa0a02e70fa4?source=rss-334463d4b90d------2">Continue reading on Medium »</a></p></div>]]></description>
            <link>https://medium.com/@pelinokutan/time-series-forecasting-with-python-practical-implementations-of-sarimax-rnn-lstm-prophet-and-aa0a02e70fa4?source=rss-334463d4b90d------2</link>
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            <category><![CDATA[long-short-term-memory]]></category>
            <category><![CDATA[sarimax]]></category>
            <category><![CDATA[recurrent-neural-network]]></category>
            <category><![CDATA[transformer-model]]></category>
            <category><![CDATA[time-series-forecasting]]></category>
            <dc:creator><![CDATA[Pelin Okutan]]></dc:creator>
            <pubDate>Wed, 04 Sep 2024 23:05:27 GMT</pubDate>
            <atom:updated>2024-09-04T23:05:27.263Z</atom:updated>
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        <item>
            <title><![CDATA[Markov Chain Monte Carlo: Made Simple Once and For All]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/@pelinokutan/markov-chain-monte-carlo-made-simple-once-and-for-all-ec90211b7012?source=rss-334463d4b90d------2"><img src="https://cdn-images-1.medium.com/max/685/0*X0qXFU55_C-2U3Nu.png" width="685"></a></p><p class="medium-feed-snippet">Markov Chain Monte Carlo (MCMC) might sound intimidating, but at its core, it&#x2019;s a powerful technique that helps us solve complex problems&#x2026;</p><p class="medium-feed-link"><a href="https://medium.com/@pelinokutan/markov-chain-monte-carlo-made-simple-once-and-for-all-ec90211b7012?source=rss-334463d4b90d------2">Continue reading on Medium »</a></p></div>]]></description>
            <link>https://medium.com/@pelinokutan/markov-chain-monte-carlo-made-simple-once-and-for-all-ec90211b7012?source=rss-334463d4b90d------2</link>
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            <category><![CDATA[mcmc-tutorial]]></category>
            <category><![CDATA[monte-carlo-method]]></category>
            <category><![CDATA[markov-chain-monte-carlo]]></category>
            <category><![CDATA[probability-sampling]]></category>
            <category><![CDATA[bayesian-inference]]></category>
            <dc:creator><![CDATA[Pelin Okutan]]></dc:creator>
            <pubDate>Wed, 21 Aug 2024 12:48:14 GMT</pubDate>
            <atom:updated>2024-08-21T12:48:14.855Z</atom:updated>
        </item>
        <item>
            <title><![CDATA[Managing Data for Effective ESG Strategies: A Guide for Modern Businesses]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/@pelinokutan/managing-data-for-effective-esg-strategies-a-guide-for-modern-businesses-1584a1595c5e?source=rss-334463d4b90d------2"><img src="https://cdn-images-1.medium.com/max/1200/0*wSUc2tOBr4oRmKbD.jpg" width="1200"></a></p><p class="medium-feed-snippet">Amid a changing global business environment, Environmental, Social, and Governance (ESG) factors have quickly become one of the most&#x2026;</p><p class="medium-feed-link"><a href="https://medium.com/@pelinokutan/managing-data-for-effective-esg-strategies-a-guide-for-modern-businesses-1584a1595c5e?source=rss-334463d4b90d------2">Continue reading on Medium »</a></p></div>]]></description>
            <link>https://medium.com/@pelinokutan/managing-data-for-effective-esg-strategies-a-guide-for-modern-businesses-1584a1595c5e?source=rss-334463d4b90d------2</link>
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            <category><![CDATA[environmental-impact]]></category>
            <category><![CDATA[corporate-governance]]></category>
            <category><![CDATA[data-driven-esg]]></category>
            <category><![CDATA[sustainability-analytics]]></category>
            <category><![CDATA[esg-data-integration]]></category>
            <dc:creator><![CDATA[Pelin Okutan]]></dc:creator>
            <pubDate>Tue, 20 Aug 2024 23:11:44 GMT</pubDate>
            <atom:updated>2024-08-20T23:11:44.568Z</atom:updated>
        </item>
        <item>
            <title><![CDATA[Integrating Bayesian Networks with Monte Carlo Simulations for Enhanced Decision-Making in…]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/@pelinokutan/integrating-bayesian-networks-with-monte-carlo-simulations-for-enhanced-decision-making-in-7f06a7e17530?source=rss-334463d4b90d------2"><img src="https://cdn-images-1.medium.com/max/1086/1*5wj4sxKl0bykbeZgO8j9KQ.png" width="1086"></a></p><p class="medium-feed-snippet">Decision-making, most of the time, is an unnecessarily overcomplicated layering of uncertainty and complexity. Be it in finance, health&#x2026;</p><p class="medium-feed-link"><a href="https://medium.com/@pelinokutan/integrating-bayesian-networks-with-monte-carlo-simulations-for-enhanced-decision-making-in-7f06a7e17530?source=rss-334463d4b90d------2">Continue reading on Medium »</a></p></div>]]></description>
            <link>https://medium.com/@pelinokutan/integrating-bayesian-networks-with-monte-carlo-simulations-for-enhanced-decision-making-in-7f06a7e17530?source=rss-334463d4b90d------2</link>
            <guid isPermaLink="false">https://medium.com/p/7f06a7e17530</guid>
            <category><![CDATA[decision-making-tools]]></category>
            <category><![CDATA[uncertainty-analysis]]></category>
            <category><![CDATA[probabilistic-modeling]]></category>
            <category><![CDATA[monte-carlo-simulation]]></category>
            <category><![CDATA[bayesian-networks]]></category>
            <dc:creator><![CDATA[Pelin Okutan]]></dc:creator>
            <pubDate>Thu, 15 Aug 2024 19:03:29 GMT</pubDate>
            <atom:updated>2024-08-15T19:03:29.682Z</atom:updated>
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