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 increased complexity 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 forecasting