Machine Learning for Business

Catalog description

Machine learning is about extracting or discovering knowledge from data. This course will cover fundamental machine learning algorithms used to understand business situations and improve business decisions. In machine learning, there are three types of commonly used algorithms: supervised (predictive), unsupervised (descriptive) and reinforcement learning algorithms. In the first part of the course, we will focus on supervised learning algorithms including K-Nearest Neighbors, Linear Regression, Logistic Regression, Decision Tree, Support Vector Machine (SVM), Naive Bayes, bagging and boosting algorithms. The second part of the course will cover unsupervised algorithms including K-means clustering and dimensionality reduction. The last part of this course will cover Reinforcement learning algorithms, especially Markov Decision Process. We will use python as our main programing language. | Prerequisites: ( MG-GY 8413 or MG-GY 9753 ) and MG-GY 8401 and Graduate Standing