With this book, you'll learn: Fundamental concepts and applications of machine learning; Advantages and shortcomings of widely used machine learning algorithms; How to represent data processed by machine learning, including which data aspects to focus on Advanced methods for model evaluation and parameter tuning; The concept of pipelines for chaining models and encapsulating your workflow Methods for working with text data, including text-specific processing techniques; Suggestions for improving your machine learning and data science skills.