Machine Learning and AI Foundations: Decision Trees with SPSS

Many data science specialists are looking to pivot toward focusing on machine learning. This course covers the essentials of machine learning, including predictive analytics and working with decision trees. Explore several popular tree algorithms and learn how to use reverse engineering to identify specific variables. Demonstrations of using the IBM SPSS Modeler are included so you can understand how decisions trees work. This course is designed to give you a solid foundation on which to build more advanced data science skills.

Topics include:
Using the SPSS Modeler
Building a CHAID model
Adding a second model with C&RT
Analysis notes
Using a lift and gains chart
Exploring algorithms
Building a tree interactively
The Bonferonni adjustment
Handling nominal, ordinal, and continuous variables
Examining the CHAID tree
The Gini coefficient
Weighing purity and balance
Understanding pruning
Examining the C&RT tree
Applying stopping rules
Using the Auto Classifier tuning trick