- How to deal with large datasets and techniques for dimension reduction
- Details on how the Bias-Variance Trade-off plays out in specific ML methods
- Models based on linear relationships, including ridge and LASSO regression
- Real-world image and text classification and how to handle time series data
Machine learning is an art that requires careful tuning and tweaking. With The Art of Machine Learning as your guide, you'll master the underlying principles of ML that will empower you to effectively use these models, rather than simply provide a few stock actions with limited practical use. Requirements: A basic understanding of graphs and charts and familiarity with the R programming language