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.