Ensemble Methods Courses and Certifications

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

Advanced Predictive Modeling: Mastering Ensembles and Metamodeling

80 ratings at LinkedIn Learning

Learn how to use ensembles and metamodeling to create more accurate predictive models.

• LinkedIn Learning
• 1 hour 11 minutes
• 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

Yannic Kilcher

Deep Ensembles: A Loss Landscape Perspective

Explore deep ensembles' effectiveness in neural networks, their superiority over Bayesian models, and how they capture non-convex loss landscapes to improve generalization and robustness in AI.

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

echohive

Prototype of a GPT Based Swarm Intelligence System as Example to Inspire More Advanced Swarm Systems

Explore a prototype GPT-based swarm intelligence system, demonstrating ensemble approaches and inspiring advanced swarm development. Includes code reviews, parallelism, and comparisons to true swarm behavior.

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

Stanford CS229 - Machine Learning Full Course Taught by Andrew Ng - Autumn 2018

Comprehensive machine learning series covering fundamental concepts to advanced topics, taught by Andrew Ng. Includes algorithms, neural networks, and reinforcement learning.

• YouTube
• 1 day 3 hours
• On-Demand
• Free Online Course

Kaggle;  Amazon Web Services

Supervised Learning

In this course, you'll learn about different types of supervised learning and how to use them to solve real-world problems.

• Udacity
• 3 weeks, 5-6 hours a week
• On-Demand
• Paid Course

Hypertuning and Cross-Validation

Master hyperparameter optimization techniques through grid search, random search, and cross-validation methods to enhance machine learning model performance and achieve optimal results.

• CodeSignal
• On-Demand
• Free Certificate

Advanced Modeling for Text Classification

Master advanced text classification using ensemble methods, deep learning, and neural networks with Python and TensorFlow. Build robust models using bagging, voting classifiers, gradient boosting, and RNNs for improved performance.

• CodeSignal
• On-Demand
• Free Certificate

Microcredential

AI Theory and Coding

Master the fundamentals of AI by implementing machine learning algorithms from scratch, covering regression, classification, optimization, ensemble methods, clustering, and neural networks with hands-on coding.

• CodeSignal
• On-Demand
• Free Certificate
• 6 courses

Microcredential

Applied Machine Learning

Develop practical machine learning skills through hands-on application of supervised learning, ensemble methods, neural networks, and advanced techniques like CNNs and reinforcement learning.

• Coursera
• On-Demand
• Paid Course
• 3 courses

Trees, SVM and Unsupervised Learning

Explore support vector machines, neural networks, decision trees, and XG boost for predictive modeling. Learn data representation through PCA and clustering for practical applications in data science.

• Coursera
• 12 hours 58 minutes
• On-Demand
• Free Online Course (Audit)

Regression Analysis

Master regression analysis techniques to model relationships, prevent overfitting, and make data-driven decisions. Explore linear and polynomial regression, regularization, cross-validation, and ensemble methods through hands-on practice.

• Coursera
• 1 day 16 hours
• On-Demand
• Free Online Course (Audit)

Machine Learning Under the Hood: The Technical Tips, Tricks, and Pitfalls

64 ratings at Coursera

Explore machine learning's technical aspects, from foundational principles to advanced methods. Learn to avoid pitfalls, interpret models, and evaluate performance while gaining insights into cutting-edge techniques and ethical considerations.

• Coursera
• 17 hours 26 minutes
• On-Demand
• Free Online Course (Audit)

Ensemble Machine Learning in Python: Random Forest, AdaBoost

2452 ratings at Udemy

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

• Udemy
• 5 hours 47 minutes
• On-Demand
• Paid Course