Super Data Science: ML & AI Podcast with Jon Krohn 681: XGBoost: The Ultimate Classifier, with Matt Harrison
May 23, 2023
Best-selling author and leading Python consultant Matt Harrison delves into XGBoost, discussing key hyperparameters, optimal modeling scenarios, and when to use/not use XGBoost. He also shares his recommended Python libraries and production tips for upgrading your data science toolkit.
Chapters
Transcript
Episode notes
1 2 3 4 5 6 7 8 9 10 11 12
Intro
00:00 • 3min
Guest's Previous Episode Success and Event Meet-ups
02:43 • 2min
Discussion on XGBoost Tuning and Deployment for Classification Models
04:51 • 4min
Exploring XGBoost Algorithm and Gradient Boosting for Classification
08:47 • 4min
Exploring Classification Problems and XGBoost in Machine Learning
12:52 • 5min
Optimizing Model Performance with Hyperparameter Tuning
17:30 • 11min
Exploring the Mechanisms and Benefits of XGBoost Algorithm
28:32 • 4min
Effectiveness of XGBoost for Tabular Data Classification
32:28 • 13min
Exploring XGBoost as a Classifier in Various Scenarios
45:35 • 2min
Optimal Usage and Limitations of XGBoost in Data Science
47:20 • 12min
Effective Communication in Data Science and Use of AI Tools
59:40 • 9min
In-depth discussion on XGBoost and related Python libraries
01:08:28 • 3min