Skip to content

Data Mining I expands predictive modeling into nonlinear dimensions, enhancing the capabilities and effectiveness of the data analytics lifecycle. In this course, learners implement supervised models—specifically classification and prediction data mining models—to unearth relationships among variables that are not apparent with more surface-leve…

Notifications You must be signed in to change notification settings

MikeMMattinson/Data_Mining_I_D209

Repository files navigation

Data_Mining_I_D209

Data Mining I expands predictive modeling into nonlinear dimensions, enhancing the capabilities and effectiveness of the data analytics lifecycle. In this course, learners implement supervised models—specifically classification and prediction data mining models—to unearth relationships among variables that are not apparent with more surface-level techniques. The course provides frameworks for assessing models’ sensitivity and specificity. D208 Predictive Modeling is a prerequisite to this course.

About

Data Mining I expands predictive modeling into nonlinear dimensions, enhancing the capabilities and effectiveness of the data analytics lifecycle. In this course, learners implement supervised models—specifically classification and prediction data mining models—to unearth relationships among variables that are not apparent with more surface-leve…

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published