Well balanced theory and practice

This is a great title that presents a holistic view of data science projects from stakeholder definition up to presentation to stakeholder about the outcome of the project. It then walks through different phases of the project and presents most common modeling techniques, some practical issues and how to tackle them using R. I think the book is full of gems whose value will be realized when someone practically faces the issues.

The book organization is well thought out as well. The chapter content is of high quality with right amount of theory and R code to apply them in practice. Data science, being a broadly scoped advanced skill, can only be learnt by doing it. Personally, being an aspiring Data Scientist, I already studied a good amount of literature on Data Mining and Big Data. However, I am not involved in any real life project. So my initial expectation was to gain the experience through case studies. However, as every project is different, you will need to juggle