XGBoost Courses and Certifications

Rob Mulla

Time Series Forecasting with XGBoost - Advanced Methods

Explore advanced time series forecasting with XGBoost, covering outlier removal, cross-validation, lag features, and future predictions. Enhance your skills in handling complex time-dependent data for improved forecasting accuracy.

• YouTube
• 22 minutes
• On-Demand
• Free Video

Rob Mulla

Time Series Forecasting with XGBoost - Use Python and Machine Learning to Predict Energy Consumption

Learn to predict energy consumption using XGBoost and Python in this hands-on tutorial. Covers data preparation, feature engineering, model building, and forecasting techniques for time series analysis.

• YouTube
• 23 minutes
• On-Demand
• Free Video

Databricks

Scaling XGBoost for Thousands of Features with Databricks

Scaling XGBoost for online advertising: Learn to handle thousands of features, optimize model training, and avoid common pitfalls in both Python and Scala implementations on Spark.

• YouTube
• 51 minutes
• On-Demand
• Free Video

Julia Silge

Feature Engineering & Interpretability for XGBoost with Board Game Ratings

Explore advanced modeling with board game ratings data: feature engineering, XGBoost tuning, and explainability methods for data-driven insights and predictive analysis.

• YouTube
• 48 minutes
• On-Demand
• Free Video

Julia Silge

Tune XGBoost With Early Stopping to Predict Shelter Animal Status

Learn to optimize xgboost models using early stopping techniques for predicting animal shelter outcomes, featuring practical examples and efficient coding strategies.

• YouTube
• 31 minutes
• On-Demand
• Free Video

Julia Silge

Tuning XGBoost Using Tidymodels

Optimize XGBoost models for beach volleyball match prediction using tidymodels, exploring data, tuning hyperparameters, and interpreting results.

• YouTube
• 51 minutes
• On-Demand
• Free Video

StatQuest with Josh Starmer

XGBoost in Python from Start to Finish

Comprehensive guide to implementing XGBoost in Python, covering data preparation, model building, and optimization techniques for effective machine learning applications.

• YouTube
• 57 minutes
• On-Demand
• Free Video

StatQuest with Josh Starmer

XGBoost Part 4 - Crazy Cool Optimizations

Explore advanced XGBoost optimizations for large datasets, including approximate algorithms, parallel learning, and sparsity-aware techniques to enhance machine learning efficiency.

• YouTube
• 24 minutes
• On-Demand
• Free Video

StatQuest with Josh Starmer

XGBoost Part 2 - Classification

Learn how XGBoost trees are built for classification, covering similarity scores, gain, cover, pruning, and logistic regression in this advanced machine learning tutorial.

• YouTube
• 25 minutes
• On-Demand
• Free Video

StatQuest with Josh Starmer

XGBoost Part 1 - Regression

Explore XGBoost's unique regression trees, focusing on similarity scores, gain calculation, pruning, regularization, and making predictions in this comprehensive tutorial.

• YouTube
• 26 minutes
• On-Demand
• Free Video

1littlecoder

XGBoost and Data Leakage in Machine Learning - Day 14 of 30 Days of ML

Explore XGBoost and data leakage in machine learning. Learn to build optimized models, prevent leakage issues, and enhance your ML skills with practical tutorials and exercises.

• YouTube
• 37 minutes
• On-Demand
• Free Video

Great Learning

Introduction to XGBoost - Machine Learning Tutorial

Comprehensive tutorial on XGBoost: from basic principles to hands-on implementation. Learn gradient boosting, parameter tuning, and model evaluation for real-world machine learning applications.

• YouTube
• 1 hour 7 minutes
• On-Demand
• Free Video

Opioid Use Disorder Prediction Using AI and Existing Risk Models

Comparative study on AI models for predicting opioid use disorder, showcasing superior performance of transformer-based AI over existing clinical tools and other machine learning approaches.

• YouTube
• 52 minutes
• On-Demand
• Free Video

Microcredential

AWS Machine Learning Engineer Nanodegree

41 ratings at Udacity

Equip developers with AWS SageMaker skills to build and deploy ML models in production. Learn data science, model design, and best practices for real-world applications.

• Udacity
• 4 months 2 weeks 5 days 11 hours 36 minutes
• On-Demand
• Paid Course

Introduction to Machine Learning

Explore machine learning concepts and workflows using AWS SageMaker, from data analysis to model deployment. Learn to apply ML techniques, use advanced algorithms, and optimize models for real-world scenarios.

• Udacity
• 4 weeks, 4-5 hours a week
• On-Demand
• Paid Course