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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!This episode is brought to you by Pathway, the reactive data processing framework, by Posit, the open-source data science company, and by Anaconda, the world's most popular Python distribution. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.In this episode you will learn:\u2022 Matt's book \u2018Effective XGBoost\u2019 [07:05]\u2022 What is XGBoost [09:09]\u2022 XGBoost's key model hyperparameters [19:01]\u2022 XGBoost's secret sauce [29:57]\u2022 When to use XGBoost [34:45]\u2022 When not to use XGBoost [41:42]\u2022 Matt\u2019s recommended Python libraries [47:36]\u2022 Matt's production tips [57:57]Additional materials: www.superdatascience.com/681