Machine Learning 2: Data Analytics & Regression

In this course, you will use statistical machine learning techniques for performing regression analysis to determine which new products are likely to be most profitable for a retailer to introduce.

In Machine Learning 2, you'll continue to build on the concepts and skills covered in Machine Learning 1:

  • Using data mining tools to investigate patterns in complex data sets
  • Preprocessing data for analytics
  • Using regression analysis to predict the unknown value of a variable
  • Applying cross-validation methods
  • Interpreting and drawing inferences from the results of data mining
  • Assessing the predictive performance of classifiers by examining key error metrics
  • Identifying where learning methods fail and gain insight into why with error analysis
  • Drawing relationships between learner performance and measured features to help understand model performance
  • Performing feature selection based on correlations between features in a dataset

This course will run from 1:00-3:00PM PDT Monday through Friday for two weeks. Course activities and class meetings are facilitated by industry experts who partner with UC Davis.

Course Code