About This Course
In this course, we'll cover advanced methods in machine learning. While linear models remain popular in industry, modern machine learning methods take advantage of increasingly complex algorithms to provide improved performance. You’ll discover advanced applications that require specialized algorithms to model them, and learn where basic techniques would result in suboptimal solutions. We’ll also explore more techniques used to improve model performance.
What You’ll Learn
Trees, bootstrap aggregation, random forests, gradient boosting and support vector machines for classification and regression
Ensemble methods and gradient boosting
How to identify frequent item sets and association rules
Clustering data using k-means and hierarchical clustering
Natural language processing, recommendation systems and reinforcement learning
