Book Image

Statistics for Data Science

Book Image

Statistics for Data Science

Overview of this book

Data science is an ever-evolving field, which is growing in popularity at an exponential rate. Data science includes techniques and theories extracted from the fields of statistics; computer science, and, most importantly, machine learning, databases, data visualization, and so on. This book takes you through an entire journey of statistics, from knowing very little to becoming comfortable in using various statistical methods for data science tasks. It starts off with simple statistics and then move on to statistical methods that are used in data science algorithms. The R programs for statistical computation are clearly explained along with logic. You will come across various mathematical concepts, such as variance, standard deviation, probability, matrix calculations, and more. You will learn only what is required to implement statistics in data science tasks such as data cleaning, mining, and analysis. You will learn the statistical techniques required to perform tasks such as linear regression, regularization, model assessment, boosting, SVMs, and working with neural networks. By the end of the book, you will be comfortable with performing various statistical computations for data science programmatically.
Table of Contents (19 chapters)
Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface

Summary


In this chapter, we started out by reviewing the idea of data structures, data models, and databases, and found similarities and differences between them.

Next, we provided an overview of machine learning and related concepts, and then compared the practice of a machine learning statistical project to a database development project.

Finally, we touched on a conceptual use of R and applying machine learning techniques to data from a database.

As this book was aimed at helping the typical data or database developer transition into the world of statistics, we hope the reader has established a sound understanding of the relevant topics in statistics and data science.

Good luck!