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        <title><![CDATA[Stories by Thomas A Dorfer on Medium]]></title>
        <description><![CDATA[Stories by Thomas A Dorfer on Medium]]></description>
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            <title>Stories by Thomas A Dorfer on Medium</title>
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            <title><![CDATA[Avoid These Easily Missed Mistakes in Machine Learning Workflows — Part 2]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/data-science/avoid-these-easily-missed-mistakes-in-machine-learning-workflows-part-2-a1c6834d3023?source=rss-7c54f9b62b90------2"><img src="https://cdn-images-1.medium.com/max/870/1*chyYE1DmC2NuFw_Ua-ks7Q.png" width="870"></a></p><p class="medium-feed-snippet">Using Unavailable Data at Prediction Time and Mixing Magic Numbers with Real Numbers</p><p class="medium-feed-link"><a href="https://medium.com/data-science/avoid-these-easily-missed-mistakes-in-machine-learning-workflows-part-2-a1c6834d3023?source=rss-7c54f9b62b90------2">Continue reading on TDS Archive »</a></p></div>]]></description>
            <link>https://medium.com/data-science/avoid-these-easily-missed-mistakes-in-machine-learning-workflows-part-2-a1c6834d3023?source=rss-7c54f9b62b90------2</link>
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            <category><![CDATA[predictive-modeling]]></category>
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            <category><![CDATA[troubleshooting]]></category>
            <category><![CDATA[data-science]]></category>
            <category><![CDATA[artificial-intelligence]]></category>
            <dc:creator><![CDATA[Thomas A Dorfer]]></dc:creator>
            <pubDate>Fri, 24 Jan 2025 11:02:07 GMT</pubDate>
            <atom:updated>2025-01-24T11:02:07.191Z</atom:updated>
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        <item>
            <title><![CDATA[Avoid These Easily Missed Mistakes in Machine Learning Workflows — Part 1]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/data-science/avoid-these-easily-missed-mistakes-in-machine-learning-workflows-part-1-1524ab299012?source=rss-7c54f9b62b90------2"><img src="https://cdn-images-1.medium.com/max/947/1*Y_Rh_hYG5DPN8NDEeuUwpw.png" width="947"></a></p><p class="medium-feed-snippet">Misusing identifiers, incorrect data splits, and ignoring rare feature values</p><p class="medium-feed-link"><a href="https://medium.com/data-science/avoid-these-easily-missed-mistakes-in-machine-learning-workflows-part-1-1524ab299012?source=rss-7c54f9b62b90------2">Continue reading on TDS Archive »</a></p></div>]]></description>
            <link>https://medium.com/data-science/avoid-these-easily-missed-mistakes-in-machine-learning-workflows-part-1-1524ab299012?source=rss-7c54f9b62b90------2</link>
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            <category><![CDATA[mlops]]></category>
            <category><![CDATA[data-science]]></category>
            <category><![CDATA[machine-learning]]></category>
            <category><![CDATA[artificial-intelligence]]></category>
            <category><![CDATA[tips-and-tricks]]></category>
            <dc:creator><![CDATA[Thomas A Dorfer]]></dc:creator>
            <pubDate>Wed, 22 Jan 2025 15:02:23 GMT</pubDate>
            <atom:updated>2025-01-22T15:02:23.269Z</atom:updated>
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            <title><![CDATA[Visualizing XGBoost Parameters: A Data Scientist’s Guide To Better Models]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/data-science/visualizing-xgboost-parameters-a-data-scientists-guide-to-better-models-38757486b813?source=rss-7c54f9b62b90------2"><img src="https://cdn-images-1.medium.com/max/937/1*I3NYEcZbRIZ3yP0-sThAeA.png" width="937"></a></p><p class="medium-feed-snippet">Why understanding parameters is critical to building robust models</p><p class="medium-feed-link"><a href="https://medium.com/data-science/visualizing-xgboost-parameters-a-data-scientists-guide-to-better-models-38757486b813?source=rss-7c54f9b62b90------2">Continue reading on TDS Archive »</a></p></div>]]></description>
            <link>https://medium.com/data-science/visualizing-xgboost-parameters-a-data-scientists-guide-to-better-models-38757486b813?source=rss-7c54f9b62b90------2</link>
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            <category><![CDATA[artificial-intelligence]]></category>
            <category><![CDATA[machine-learning]]></category>
            <category><![CDATA[software-development]]></category>
            <category><![CDATA[xgboost]]></category>
            <category><![CDATA[data-science]]></category>
            <dc:creator><![CDATA[Thomas A Dorfer]]></dc:creator>
            <pubDate>Wed, 15 Jan 2025 11:02:45 GMT</pubDate>
            <atom:updated>2025-01-16T12:16:00.892Z</atom:updated>
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        <item>
            <title><![CDATA[Bagging vs. Boosting: The Power of Ensemble Methods in Machine Learning]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://pub.towardsai.net/bagging-vs-boosting-the-power-of-ensemble-methods-in-machine-learning-6404e33524e6?source=rss-7c54f9b62b90------2"><img src="https://cdn-images-1.medium.com/max/1153/1*XzaoQxMf4uLD5DIHz8JwbA.png" width="1153"></a></p><p class="medium-feed-snippet">How to maximize predictive performance by creating a strong learner from multiple weak ones</p><p class="medium-feed-link"><a href="https://pub.towardsai.net/bagging-vs-boosting-the-power-of-ensemble-methods-in-machine-learning-6404e33524e6?source=rss-7c54f9b62b90------2">Continue reading on Towards AI »</a></p></div>]]></description>
            <link>https://pub.towardsai.net/bagging-vs-boosting-the-power-of-ensemble-methods-in-machine-learning-6404e33524e6?source=rss-7c54f9b62b90------2</link>
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            <category><![CDATA[artificial-intelligence]]></category>
            <category><![CDATA[data-science]]></category>
            <category><![CDATA[machine-learning]]></category>
            <category><![CDATA[science]]></category>
            <category><![CDATA[technology]]></category>
            <dc:creator><![CDATA[Thomas A Dorfer]]></dc:creator>
            <pubDate>Fri, 16 Jun 2023 14:03:46 GMT</pubDate>
            <atom:updated>2023-06-16T14:03:46.125Z</atom:updated>
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        <item>
            <title><![CDATA[Ten Years of AI in Review]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/data-science/ten-years-of-ai-in-review-85decdb2a540?source=rss-7c54f9b62b90------2"><img src="https://cdn-images-1.medium.com/max/1209/1*PhCR6zOAz5QaJUfJFBEQPQ.png" width="1209"></a></p><p class="medium-feed-snippet">From image classification to chatbot therapy</p><p class="medium-feed-link"><a href="https://medium.com/data-science/ten-years-of-ai-in-review-85decdb2a540?source=rss-7c54f9b62b90------2">Continue reading on TDS Archive »</a></p></div>]]></description>
            <link>https://medium.com/data-science/ten-years-of-ai-in-review-85decdb2a540?source=rss-7c54f9b62b90------2</link>
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            <category><![CDATA[artificial-intelligence]]></category>
            <category><![CDATA[technology]]></category>
            <category><![CDATA[editors-pick]]></category>
            <category><![CDATA[machine-learning]]></category>
            <category><![CDATA[deep-learning]]></category>
            <dc:creator><![CDATA[Thomas A Dorfer]]></dc:creator>
            <pubDate>Tue, 23 May 2023 14:04:59 GMT</pubDate>
            <atom:updated>2023-05-23T14:04:59.696Z</atom:updated>
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            <title><![CDATA[YOLO-NAS: How to Achieve the Best Performance on Object Detection Tasks]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/data-science/yolo-nas-how-to-achieve-the-best-performance-on-object-detection-tasks-6b95347908d4?source=rss-7c54f9b62b90------2"><img src="https://cdn-images-1.medium.com/max/1891/1*R8fBanPjts-Io5FEdjJbOg.png" width="1891"></a></p><p class="medium-feed-snippet">A foundational model generated through neural architecture search, innovative quantization blocks, and a robust pre-training paradigm</p><p class="medium-feed-link"><a href="https://medium.com/data-science/yolo-nas-how-to-achieve-the-best-performance-on-object-detection-tasks-6b95347908d4?source=rss-7c54f9b62b90------2">Continue reading on TDS Archive »</a></p></div>]]></description>
            <link>https://medium.com/data-science/yolo-nas-how-to-achieve-the-best-performance-on-object-detection-tasks-6b95347908d4?source=rss-7c54f9b62b90------2</link>
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            <category><![CDATA[machine-learning]]></category>
            <category><![CDATA[data-science]]></category>
            <category><![CDATA[artificial-intelligence]]></category>
            <category><![CDATA[yolo-nas]]></category>
            <category><![CDATA[computer-vision]]></category>
            <dc:creator><![CDATA[Thomas A Dorfer]]></dc:creator>
            <pubDate>Fri, 19 May 2023 03:45:18 GMT</pubDate>
            <atom:updated>2023-05-19T03:45:18.330Z</atom:updated>
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            <title><![CDATA[Quick and Easy Time-Series Forecasting in PowerBI: A Practical Guide]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/data-science/quick-and-easy-time-series-forecasting-in-powerbi-a-practical-guide-c31a858ee220?source=rss-7c54f9b62b90------2"><img src="https://cdn-images-1.medium.com/max/939/1*0n8fDB_83Ppe9bgM4MPI1Q.png" width="939"></a></p><p class="medium-feed-snippet">How to set up and configure a forecasting system in just a few clicks</p><p class="medium-feed-link"><a href="https://medium.com/data-science/quick-and-easy-time-series-forecasting-in-powerbi-a-practical-guide-c31a858ee220?source=rss-7c54f9b62b90------2">Continue reading on TDS Archive »</a></p></div>]]></description>
            <link>https://medium.com/data-science/quick-and-easy-time-series-forecasting-in-powerbi-a-practical-guide-c31a858ee220?source=rss-7c54f9b62b90------2</link>
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            <category><![CDATA[forecasting]]></category>
            <category><![CDATA[technology]]></category>
            <category><![CDATA[data-science]]></category>
            <category><![CDATA[power-bi]]></category>
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            <dc:creator><![CDATA[Thomas A Dorfer]]></dc:creator>
            <pubDate>Mon, 01 May 2023 15:05:55 GMT</pubDate>
            <atom:updated>2023-05-01T15:05:55.323Z</atom:updated>
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            <title><![CDATA[How to Choose the Best Evaluation Metric for Regression Problems]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/data-science/how-to-choose-the-best-evaluation-metric-for-regression-problems-b9f2e60e25ef?source=rss-7c54f9b62b90------2"><img src="https://cdn-images-1.medium.com/max/1201/1*rVTCIffI2D_-i_CGeHwF6A.png" width="1201"></a></p><p class="medium-feed-snippet">A comprehensive guide covering the most commonly used evaluation metrics used in regression and their utility in different scenarios</p><p class="medium-feed-link"><a href="https://medium.com/data-science/how-to-choose-the-best-evaluation-metric-for-regression-problems-b9f2e60e25ef?source=rss-7c54f9b62b90------2">Continue reading on TDS Archive »</a></p></div>]]></description>
            <link>https://medium.com/data-science/how-to-choose-the-best-evaluation-metric-for-regression-problems-b9f2e60e25ef?source=rss-7c54f9b62b90------2</link>
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            <category><![CDATA[machine-learning]]></category>
            <category><![CDATA[technology]]></category>
            <category><![CDATA[metrics]]></category>
            <category><![CDATA[data-science]]></category>
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            <dc:creator><![CDATA[Thomas A Dorfer]]></dc:creator>
            <pubDate>Mon, 24 Apr 2023 15:05:16 GMT</pubDate>
            <atom:updated>2023-04-24T15:05:16.063Z</atom:updated>
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        <item>
            <title><![CDATA[How to Choose the Best Evaluation Metric for Classification Problems]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/data-science/how-to-choose-the-best-evaluation-metric-for-classification-problems-638e845da334?source=rss-7c54f9b62b90------2"><img src="https://cdn-images-1.medium.com/max/1370/1*XVxupIhybCaMtarsZFk22g.png" width="1370"></a></p><p class="medium-feed-snippet">A comprehensive guide covering the most commonly used evaluation metrics for supervised classification and their utility in different&#x2026;</p><p class="medium-feed-link"><a href="https://medium.com/data-science/how-to-choose-the-best-evaluation-metric-for-classification-problems-638e845da334?source=rss-7c54f9b62b90------2">Continue reading on TDS Archive »</a></p></div>]]></description>
            <link>https://medium.com/data-science/how-to-choose-the-best-evaluation-metric-for-classification-problems-638e845da334?source=rss-7c54f9b62b90------2</link>
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            <category><![CDATA[machine-learning]]></category>
            <category><![CDATA[metrics]]></category>
            <category><![CDATA[editors-pick]]></category>
            <category><![CDATA[classification]]></category>
            <category><![CDATA[artificial-intelligence]]></category>
            <dc:creator><![CDATA[Thomas A Dorfer]]></dc:creator>
            <pubDate>Mon, 17 Apr 2023 18:16:55 GMT</pubDate>
            <atom:updated>2023-04-17T18:16:55.671Z</atom:updated>
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        <item>
            <title><![CDATA[Auto-Sklearn: How To Boost Performance and Efficiency Through Automated Machine Learning]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/data-science/auto-sklearn-how-to-boost-performance-and-efficiency-through-automated-machine-learning-2db116eafc8?source=rss-7c54f9b62b90------2"><img src="https://cdn-images-1.medium.com/max/1200/1*BpWNDjTHoqR6dGQVLcbl_w.jpeg" width="1200"></a></p><p class="medium-feed-snippet">Learn how to leverage AutoML to maximize the outcome of your machine learning workflows</p><p class="medium-feed-link"><a href="https://medium.com/data-science/auto-sklearn-how-to-boost-performance-and-efficiency-through-automated-machine-learning-2db116eafc8?source=rss-7c54f9b62b90------2">Continue reading on TDS Archive »</a></p></div>]]></description>
            <link>https://medium.com/data-science/auto-sklearn-how-to-boost-performance-and-efficiency-through-automated-machine-learning-2db116eafc8?source=rss-7c54f9b62b90------2</link>
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            <category><![CDATA[data-science]]></category>
            <category><![CDATA[python]]></category>
            <category><![CDATA[machine-learning]]></category>
            <category><![CDATA[artificial-intelligence]]></category>
            <category><![CDATA[hands-on-tutorials]]></category>
            <dc:creator><![CDATA[Thomas A Dorfer]]></dc:creator>
            <pubDate>Tue, 11 Apr 2023 13:27:25 GMT</pubDate>
            <atom:updated>2023-04-11T13:27:25.776Z</atom:updated>
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