Practical Data Science with R

Table of Contents

PART 1 INTRODUCTION TO DATA SCIENCE

• 1 The data science process

• 2 Loading data into R

• 3 Exploring data

• 4 Managing data

PART 2 MODELING METHODS

• 5 Choosing and evaluating models

• 6 Memorization methods

• 7 Linear and logistic regression

• 8 Unsupervised methods

• 9 Exploring advanced methods

PART 3 DELIVERING RESULTS

• 10 Documentation and deployment

• 11 Producing effective presentations