R Books

If you know how to program, you have the skills to turn data into knowledge. This thoroughly revised edition presents statistical concepts computationally, rather than mathematically, using programs written in Python. Through practical examples and exercises based on real-world datasets, you'll learn the entire process of exploratory data analysis

Get going with tidymodels, a collection of R packages for modeling and machine learning. Whether you're just starting out or have years of experience with modeling, this practical introduction shows data analysts, business analysts, and data scientists how the tidymodels framework offers a consistent, flexible approach for your work. RStudio engine

GitOps delivers on the vision promised to a DevOps culture, and while the practice isn't new, organizations are starting to realize how valuable it is to deliver products in a fast, highly automated, and secure way - without compromising the quality of their code. This book outlines the tools, workflows, and structures that teams need to have in pl

The DSC Book is a comprehensive and continually evolving guide to Microsoft's Desired State Configuration (DSC) technology. Authored by Don Jones and Steve Murawski, this mini book demystifies the powerful declarative platform designed for automating the configuration and management of infrastructure across on-premises and cloud environments. It co

Principles of Data Science is intended to support one- or two-semester courses in data science. It is appropriate for data science majors and minors as well as students concentrating in business, finance, health care, engineering, the sciences, and a number of other fields where data science has become critically important. The authors have include

This book is about dynamic programming and its applications in economics, finance, and adjacent fields. It brings together recent innovations in the theory of dynamic programming and provides applications and code that can help readers approach the research frontier. The book is aimed at graduate students and researchers, although most chapters are

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

Elements of Data Science is an introduction to the practical skills of working with data, written for people with no programming experience. Concepts are explained clearly and concisely, and exercises in each chapter demonstrate the real-world use of each feature. - Step-by-Step Approach: Learn how to execute a data science project from start to fi

Workplace Software and Skills is designed to flexibly support a range of courses covering computer literacy, Microsoft Office, and Google Suite applications. The textbook covers both hard and soft skills that are applicable to a broad range of academic majors and careers. Chapters combine studio learning and guided practice with scaffolded activiti

As generative artificial intelligence (AI) rapidly transforms legal practice, the profession faces opportunities and challenges in adopting these technologies. GenAI for Legal Practice provides a comprehensive and accessible guide to integrating generative AI tools into Australian legal practice, offering both theoretical foundations and practical