681: XGBoost: The Ultimate Classifier, with Matt Harrison

<p>Unlock the power of XGBoost by learning how to fine-tune its hyperparameters and discover its optimal modeling situations. This and more, when best-selling author and leading Python consultant Matt Harrison teams up with Jon Krohn for yet another jam-packed technical episode! Are you ready to upgrade your data science toolkit in just one hour? Tune-in now!<br/><br/>This episode is brought to you by <a href='https://pathway.com/?from=superdatascience'>Pathway</a>, the reactive data processing framework, by <a href='https://posit.co/'>Posit</a>, the open-source data science company, and by <a href='https://superdatascience.com/anaconda'>Anaconda</a>, the world&apos;s most popular Python distribution. Interested in sponsoring a SuperDataScience Podcast episode? Visit <a href='https://jonkrohn.com/podcast'>JonKrohn.com/podcast</a> for sponsorship information.<br/><br/>In this episode you will learn:<br/>• Matt&apos;s book ‘Effective XGBoost’ [07:05]<br/>• What is XGBoost [09:09]<br/>• XGBoost&apos;s key model hyperparameters [19:01]<br/>• XGBoost&apos;s secret sauce [29:57]<br/>• When to use XGBoost [34:45]<br/>• When not to use XGBoost [41:42]<br/>• Matt’s recommended Python libraries [47:36]<br/>• Matt&apos;s production tips [57:57]<br/><br/>Additional materials: <a href='https://www.superdatascience.com/681'>www.superdatascience.com/681</a></p>