Data Science & AI Books

Modern Data Visualization with R describes the many ways that raw and summary data can be turned into visualizations that convey meaningful insights. It starts with basic graphs such as bar charts, scatter plots, and line charts, but progresses to less well-known visualizations such as tree maps, alluvial plots, radar charts, mosaic plots, effects

First Semester in Numerical Analysis with Julia presents the theory and methods, together with the implementation of the algorithms using the Julia programming language. The open access book covers computer arithmetic, root-finding, numerical quadrature and differentiation, and approximation theory. The reader is expected to have studied calculus a

This practical guide bridges the core concepts of Digital Signal Processing (DSP) and modern digital communications. It focuses on the implementation of these principles using open-source tools like Python, Octave, and GNU Radio, alongside low-cost hardware platforms (USRP, DVB-T dongles, HackRF). The book takes a hands-on, code-first approach to b

What exactly is business analytics? The business part is easy; it means a commercial operation or a company. Business is often associated with entrepreneurship and management. Business analytics is a new, expanding subfield with fuzzy edges that overlap into a variety of other established disciplines, including economics, econometrics, computer sci

This open access book explores the latest advancements and challenges in standardized methodologies, efficient code management, and scalable data processing of neuroimaging datasets. The chapters in this book are organized in four parts. Part One shows the researcher how to access and download large datasets, and how to compute at scale. Part Two c

This open access book presents the concept of Informed Machine Learning and demonstrates its practical use with a compelling collection of applications of this paradigm in industrial and business use cases. These range from health care over manufacturing and material science to more advanced combinations with deep learning, say, in the form of phys

Turn your R code into packages that others can easily install and use. With this fully updated edition, developers and data scientists will learn how to bundle reusable R functions, sample data, and documentation together by applying the package development philosophy used by the team that maintains the "tidyverse" suite of packages. In the process

This open access volume explains the foundations of modern solvers for ordinary differential equations (ODEs). Formulating and solving ODEs is an essential part of mathematical modeling and computational science, and numerous solvers are available in commercial and open source software. However, no single ODE solver is the best choice for every sin

The current period of progress in artificial intelligence was triggered when Krizhevsky et al. demonstrated that an artificial neural network designed twenty years earlier could outperform complex state-of-the-art image recognition methods by a huge margin, simply by being a hundred times larger and trained on a dataset similarly scaled up. This br

This open cookbook provides more than 150 recipes to help scientists, engineers, programmers, and data analysts generate high-quality graphs quickly - without having to comb through all the details of R's graphing systems. Each recipe tackles a specific problem with a solution you can apply to your own project and includes a discussion of how and w