Ensemble Learning Courses and Certifications

Ensemble Machine Learning in Python: Random Forest, AdaBoost

2653 ratings at Udemy

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

• Udemy
• 5 hours 48 minutes
• On-Demand
• Paid Course

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

Great Learning

Ensemble Learning - Decision Tree Algorithm - Gini Index

Master ensemble learning techniques, decision trees, and boosting methods. Hands-on demos with real datasets enhance understanding of these powerful machine learning concepts for improved model performance.

• YouTube
• 3 hours 24 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

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
• 3 hours
• On-Demand
• Free Certificate

Coursera

Optimize AI: Build Robust Ensemble Models

Unlock advanced ensemble modeling techniques to balance performance with interpretability while mastering statistical validation for production AI systems.

• Coursera
• 1 hour 55 minutes
• On-Demand
• Paid Course

DigitalSreeni

Improving Semantic Segmentation - U-Net Performance via Ensemble of Multiple Trained Networks

Enhance U-Net performance for semantic segmentation using ensemble methods with ResNet34, Inception V3, and VGG16 networks. Includes code, dataset, and practical implementation tips.

• YouTube
• 30 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

NPTEL-NOC IITM

Bagging (Bootstrap Aggregating)

Explore the concept of Bagging (Bootstrap AGGregatING), its working, hyperparameters, OOB error estimation, advantages, limitations, and relationship to Random Forests.

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

Introduction to Machine Learning with Azure

8 ratings at Udacity

Explore machine learning fundamentals and hands-on Azure ML Studio training, covering data preparation, model development, and responsible AI principles.

• Udacity
• 22 hours
• On-Demand
• Free Online Course

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

Microcredential

Introduction to Machine Learning with SciKit Learn

246 ratings at CodeSignal

Master machine learning fundamentals using SciKit-learn, from data preprocessing through advanced model evaluation, including regression, classification, ensemble methods and hyperparameter tuning.

• CodeSignal
• 18 hours
• On-Demand
• Free Certificate
• 7 courses

Association for Computing Machinery (ACM)

FADE - FAir Double Ensemble Learning for Observable and Counterfactual Outcomes

Learn a novel machine learning approach for fair prediction of both observable and counterfactual outcomes, enhancing decision-making in various domains.

• YouTube
• 15 minutes
• On-Demand
• Conference Talk

UofU Data Science

Boosting and Ensemble Methods in Machine Learning - Lecture 18

Dive into boosting algorithms and learn how to combine weak learning rules to create powerful predictive models in machine learning applications.

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

UofU Data Science

Machine Learning: Boosting and Ensemble Methods - Lecture 19

Dive into advanced boosting techniques and ensemble methods to transform weak learning algorithms into powerful predictive models for enhanced machine learning capabilities.

• YouTube
• 1 hour 18 minutes
• On-Demand
• Free Video