Supervised and unsupervised machine learning is explored. Discussion covers standard data mining techniques using machine learning algorithms, including correlation and association, discriminant analysis, naïve Bayes, nearest neighbor, cluster analysis, decision trees, and neural networks. Text mining is also covered.
At the end of the course, you’re expected to:
- Comprehend the mechanics of machine learning, and multiple techniques such as pattern recognition, or statistical hypothesis testing.
- Apply the data requirements for regressions, classification, and clustering machine learning activities.
- Implement data cleansing, normalization, and standardization techniques.
- Evaluate model accuracy and implement improvements.
- Apply advanced modeling techniques to a variety of business activities.
Prerequisite: MBA616 Principles of Economics and Marketing, MBA 618 Business Statistics, and BIA 630 Data Analysis and Business Modelling