Chapter 1, Acquire and Prepare the Ingredients – Reading Your Data, provides the recipes to acquire, format, and cleanse data from multiple formats. Handling missing values, standardizing datasets, and transforming between numerical and categorical data are also covered.
Chapter 2, What's in There? – Exploratory Data Analysis, shows you how to perform exploratory data analysis and find underlying patterns to understand our dataset before getting into the analysis process.
Chapter 3, Where does it belong? - Classification, covers several classification techniques from basic classification trees, logistic regression, and support vector machines to text classification using Naive Bayes to find sentiment analysis.
