"The purpose of this chapter is to introduce the fundamentals of the R programming language, and the basic tools you will need to use this book; it is therefore an important chapter for readers new to R. The reader is advised, following reading this chapter, to proceed to Chapter 2 which,...

"Deep learning is rapidly gaining momentum in the world of finance and trading. But for many professional traders, this sophisticated field has a reputation for being complex and difficult. This hands-on guide teaches you how to develop a deep learning trading model from scratch using Python,...

"By moving away from flawed statistical methodologies, you'll move toward an intuitive view of probability as a mathematically rigorous statistical framework that quantifies uncertainty holistically and successfully. This book shows you how."

"Businesses typically encounter problems first and then seek out analytical methods to help in decision making. Business Analytics: Solving Business Problems with R by Arul Mishra and Himanshu Mishra offers practical, data-driven solutions for today's dynamic business environment. This text...

Data Science for Business with R, written by Jeffrey S. Saltz and Jeffrey M. Stanton, focuses on the concepts foundational for students starting a business analytics or data science degree program. To keep the book practical and applied, the authors feature a running case using a global airline...

"Econophysics explores the parallels between physics and economics and is an exciting topic that is attracting increasing attention. However there is a lack of literature that explains the topic from a broad perspective. This book introduces advanced undergraduates and graduate students in...