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Predictive Modeling with Ensembles: Advanced Techniques for Deeper Insights

Duration: One Day Course

Prerequisite: None

Ensembling is one of the hottest techniques in today’s predictive analytics competitions.  Every single recent winner of Kaggle.com and KDD competitions used an ensemble technique, including famous algorithms such as XGBoost, Random Forest, and “Deep Stacking”.

Are these competition victories paving the way for widespread organizational implementation of these techniques? Yes, but not entirely. We will walk through an effective and practical approach to ensembling most applicable to organizational problems, attainable by analytic practitioners and adoptable by leadership.

This course will provide a detailed overview of ensemble models, their origin, and show why they are so effective. We will explain the building blocks of virtually all ensembles techniques: bagging, boosting, and stacking.
While not a prerequisite, attending the “Decision Trees in Machine Learning” course provides a great foundation of machine learning and supervised learning techniques prior to this session.

What You Will Learn

  • What are ensemble models and what are their advantages?
  • Why are ensembles in the news?
  • Three influential ensembling approaches and three famous algorithms
  • The core elements of ensembles and their application – bagging, boosting, and stacking
  • How to apply “meta-modeling” to real-world problems
  • The pros and cons of complex "black box" techniques in solving business problems
  • The challenge of applying competition strategies to organizational problems
  • Case Study: Using an ensemble to address systematically missing data

Geared To

  • Analytic Practitioners; Data Scientists; IT Professionals; Technology Planners; Consultants; Business Analysts; Analytic Project Leaders

Contact Us to Get Started Today

REQUEST INFORMATION

Yvonne Baho

Yvonne M. Baho Director, Enterprise Learning
Phone: 978.582.7105
Email: ybaho@tdwi.org

TESTIMONIALS

"The instructor was very responsive to input from the class and adapted to meet the needs specific to our context. I especially appreciated the many case studies and focus on assessment."

S. Bessias UNC Healthcare

"Very good overall view of DW concepts and provided valuable insight for such a varied audience."

Jerry Bundt Nestle Purina

"This was the best training class I’ve had in my 20 year career."

Tim Grieb Seattle Children’s Hospital

"The instructor did an excellent job and demonstrated an understanding of real world applications."

Sean Dewulf Con-way Freight

REQUEST INFORMATION

Yvonne Baho Yvonne M. Baho
Director, Enterprise Learning
Phone: 978.582.7105
E-mail: ybaho@tdwi.org
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