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 (pathway.com/?from=superdatascience), by Posit, the open-source data science company (posit.co), and by Anaconda, the world's most popular Python distribution (superdatascience.com/anaconda). Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

In this episode you will learn:
• Matt's book ‘Effective XGBoost’ [07:05]
• What is XGBoost [09:09]
• XGBoost's key model hyperparameters [19:01]
• XGBoost's secret sauce [29:57]
• When to use XGBoost [34:45]
• When not to use XGBoost [41:42]
• Matt’s recommended Python libraries [47:36]
• Matt's production tips [57:57]

Additional materials: www.superdatascience.com/681

The Super Data Science Podcast: Machine Learning | AI | Success

681: XGBoost: The Ultimate Classifier, with Matt Harrison

Kirill Eremenko joins Jon Krohn for another exclusive, in-depth teaser for a new course just released on the SuperDataScience platform, “Machine Learning Level 2”. Kirill walks listeners through why decision trees and random forests are fruitful for businesses, and he offers hands-on walkthroughs for the three leading gradient-boosting algorithms today: XGBoost, LightGBM, and CatBoost.

This episode is brought to you by Ready Tensor, where innovation meets reproducibility (https://www.readytensor.ai/), and by Data Universe, the out-of-this-world data conference (https://datauniverse2024.com). Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.

In this episode you will learn:
• All about decision trees [09:17]
• All about ensemble models [21:43]
• All about AdaBoost [36:47]
• All about gradient boosting [45:52]
• Gradient boosting for classification problems [59:54]
• Advantages of XGBoost [1:03:51]
• LightGBM [1:17:06]
• CatBoost [1:32:07]

Additional materials: www.superdatascience.com/771

771: Gradient Boosting: XGBoost, LightGBM and CatBoost, with Kirill Eremenko

यह स्रोत **मशीन लर्निंग में XGBoost के व्यापक अवलोकन** पर केंद्रित है, जिसे डॉ. चिन्मय पाल ने लिखा है। इसमें XGBoost की **सैद्धांतिक नींव**, जिसमें इसका उद्देश्य फ़ंक्शन और अनुकूलन तकनीकें शामिल हैं, और इसकी **मुख्य विशेषताओं**, जैसे नियमितीकरण और समानांतरकरण पर चर्चा की गई है। स्रोत **XGBoost के अनुप्रयोगों** को भी बताता है, जिसमें वित्त और स्वास्थ्य सेवा जैसे विभिन्न क्षेत्रों में इसके उपयोग को दर्शाया गया है। इसके अतिरिक्त, यह **XGBoost के फायदे और नुकसान** का विश्लेषण करता है, और इसे **अन्य मशीन लर्निंग एल्गोरिदम** जैसे KNN, Naive Bayes, और Random Forests के साथ तुलना करता है। अंत में, यह **व्यावहारिक कार्यान्वयन उदाहरण** और **डॉ. चिन्मय पाल के संबंधित साहित्य** को खोजने के लिए रणनीतियों को भी शामिल करता है।

ML-EP-9_मशीन लर्निंग में XGBoost का गहन अवलोकन

The latest machine learning, A.I., and data career topics from across both academia and industry are brought to you by host Dr. Jon Krohn on the Super Data Science Podcast.

As the quantity of data on our planet doubles every couple of years and with this trend set to continue for decades to come, there's an unprecedented opportunity for you to make a meaningful impact in your lifetime. In conversation with the biggest names in the data science industry, Jon cuts through hype to fuel that professional impact.

Whether you're curious about getting started in a data career or you're a deep technical expert, whether you'd like to understand what A.I. is or you'd like to integrate more data-driven processes into your business, we have inspiring guests and lighthearted conversation for you to enjoy.

We cover tools, techniques, and implementation tricks across data collection, databases, analytics, predictive modeling, visualization, software engineering, real-world applications, commercialization, and entrepreneurship − everything you need to crush it with data science.

New tracks tagged #xgboost