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Hands-On Machine Learning: Harnessing the Power of Big Data for Inference (NEW)

Duration: Three Day Course

Prerequisite: Basic Python, basic to intermediate statistics, basic linear algebra, and/or successful completion of the Introduction to Predictive Analytics course

In a world with abundant data, leveraging machines to learn valuable patterns from structured data can be extremely powerful. We explore the basics of machine learning, discussing concepts like regression, classification, model evaluation metrics, overfitting, variance versus bias, linear regression, ensemble methods, model selection, and hyperparameter optimization.

Through powerful packages such as scikit-learn, students come away with a strong understanding of core concepts in machine learning as well as the ability to efficiently train and benchmark accurate predictive models. They gain hands-on experience building complex ETL pipelines to handle data in a variety of formats; developing models with tools like feature unions and pipelines to reduce duplicate work; and practicing tricks like parallelization to speed up prototyping and development.

You Will Learn

  • Core machine learning concepts
  • A survey of ML modeling techniques
  • Production-grade ML pipeline development

Geared To

  • Individuals comfortable with basic programming and statistics looking to leverage machine-learning techniques for greater data insights

Technology Requirements

  • All attendees must have a laptop with Google Chrome installed
  • Classroom must be equipped with WiFi and an HDMI enabled projector

Contact Us to Get Started Today

REQUEST INFORMATION

Yvonne Baho

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

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TESTIMONIALS

“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

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