Bagging Courses and Certifications

Ensemble Methods in Python

1 review

Learn how to build advanced and effective machine learning models in Python using ensemble techniques such as bagging, boosting, and stacking.

• DataCamp
• 4 hours
• On-Demand
• Free Trial Available

Ensemble Methods from Scratch

Master ensemble methods by building Bagging, Random Forest, AdaBoost, and Gradient Boosting implementations from scratch. Learn to enhance predictive models through hands-on coding without relying on libraries.

• CodeSignal
• On-Demand
• Free Certificate

Ensembles in Machine Learning

Master ensemble learning techniques like bagging, boosting, and stacking to enhance predictive modeling performance, from Random Forests to Gradient Boosting and AdaBoost implementations.

• CodeSignal
• On-Demand
• Free Certificate

Ensemble Machine Learning in Python: Random Forest, AdaBoost

2640 ratings at Udemy

Ensemble Methods: Boosting, Bagging, Boostrap, and Statistical Machine Learning for Data Science in Python

• Udemy
• 5 hours 50 minutes
• On-Demand
• Paid Course

Sungkyunkwan University

Machine Learning for Smart Beta

Explore smart beta products, recreate MSCI Enhanced Value Index, and apply machine learning techniques to create improved multi-factor models for investment strategies using R programming.

• Coursera
• 7 hours 30 minutes
• On-Demand
• Free Online Course (Audit)

Decision Trees, Random Forests, Bagging & XGBoost: R Studio

237 ratings at Udemy

Decision Trees and Ensembling techinques in R studio. Bagging, Random Forest, GBM, AdaBoost & XGBoost in R programming

• Udemy
• 5 hours 54 minutes
• On-Demand
• Paid Course

Fractal Analytics

Advanced Machine Learning Algorithms

Explore advanced machine learning algorithms, from regularization to ensemble methods. Master feature engineering, hyperparameter tuning, and model selection for enhanced predictive accuracy and real-world applications.

• Coursera
• 20 hours 43 minutes
• On-Demand
• Free Online Course (Audit)

Applied Machine Learning: Ensemble Learning

166 ratings at LinkedIn Learning

Explore how to make powerful, accurate predictions with ensemble learners, one of the most common classes of machine learning algorithms.

• LinkedIn Learning
• 2 hours 26 minutes
• On-Demand
• Free Trial Available

Machine Learning and AI: Advanced Decision Trees with SPSS

68 ratings at LinkedIn Learning

Work toward a mastery of machine learning by exploring advanced decision tree algorithm concepts. Learn about the QUEST and C5.0 algorithms and a few advanced topics.

• LinkedIn Learning
• 1-2 hours
• On-Demand
• Free Trial Available

Explore ensemble techniques like bagging, boosting, and stacking to enhance machine learning model performance using random forests and advanced methods.

• Codecademy
• 2 hours
• On-Demand
• Free Trial Available

Great Learning

Boosting

Explore ensemble learning techniques like boosting to enhance machine learning performance. Learn about bias, variance, and popular algorithms for improved model accuracy and decision-making.

• YouTube
• 1 hour 44 minutes
• On-Demand
• Free Video

Great Learning

Bagging and Boosting

Explore ensemble learning techniques like bagging and boosting to improve machine learning model performance. Learn how to combine multiple algorithms for better results across various domains.

• YouTube
• 1 hour 35 minutes
• On-Demand
• Free Video

Decision Trees and Ensemble Methods

Explore decision trees, ensemble methods, and advanced techniques like random forests and boosting algorithms for improved machine learning model performance.

• YouTube
• 2 hours 30 minutes
• On-Demand
• Free Video

Software Engineering Courses - SE Courses

Logistic Regression and Ensemble Learning - Bagging and Boosting - AdaBoost

Explore logistic regression, ensemble learning, bagging, and boosting in this AI/ML course. Learn AdaBoost and decision stumps for strong non-linear classification.

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

Julia Silge

Predict Astronauts' Mission Duration With Tidymodels and Bootstrap Aggregation

Explore astronaut mission duration prediction using R's tidymodels and bootstrap aggregation, featuring data analysis, preprocessing, and model evaluation techniques.

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