A complete foundation for Statistics, also serving as a foundation for Data Science. Leanpub revenue supports OpenIntro (US-based nonprofit) so we can provide free desk copies to teachers interested in using OpenIntro Statistics in the classroom and expand the project to support free textbooks in other subjects. More resources: openintro.org.
The Windows 11 Field Guide is a full-length e-book about the latest version of Microsoft Windows, aimed at those users who will upgrade from Windows 10 or acquire Windows 11 with a new PC.
Data analysis is now part of practically every research project in the life sciences. In this book we use data and computer code to teach the necessary statistical concepts and programming skills to become a data analyst. Instead of showing theory first and then applying it to toy examples, we start with actual applications and describe the theory as it becomes necessary to solve specific challenges. The book includes links to computer code that readers can use to follow along as they program.
IT'S A HIGHWAY TO A BETTER COFFEE AND ROASTING! It's filled with practical advice of 12 years roasting experience that's made simple to accelerate your learning in coffee roasting.
Have you ever been curious about how your phone unlocks when it sees your face, how a camera can track people and objects in a video, how humans see depth, or how computers can differentiate dogs from cats? This book will start from the basics of image manipulation and build up to cover all of these topics, and more!
The book provides a modern look at introductory Biostatistical concepts and the associated computational tools using the latest developments in computation and visualization in the R language environment. The book includes practical data analysis based on datasets that can be downloaded here: https://github.com/muschellij2/biostatmethods.
The book provides a modern look at introductory Biostatistical concepts and the associated computational tools using the latest developments in computation and visualization in the R language environment. The book includes practical data analysis based on datasets that can be downloaded here: https://github.com/muschellij2/biostatmethods.
This book brings the fundamentals of R programming to you, using the same material developed as part of the industry-leading Johns Hopkins Data Science Specialization. The skills taught in this book will lay the foundation for you to begin your journey learning data science. Printed copies of this book are available through Lulu.
This book teaches you to use R to effectively visualize and explore complex datasets. Exploratory data analysis is a key part of the data science process because it allows you to sharpen your question and refine your modeling strategies. This book is based on the industry-leading Johns Hopkins Data Science Specialization.
The official companion of Finding Hidden Messages in DNA, the popular first course in Coursera's Bioinformatics sequence. Learn how biologists have begun to decipher the strange and wonderful language of DNA without needing to put on a lab coat. This book contains the first two chapters from Volume 1 of Bioinformatics Algorithms: An Active Learning Approach.
A structured introduction to the foundations of civil, criminal, and business law. This book breaks down essential legal principles in a clear and accessible way, helping readers understand how the law functions in real-world situations. Designed for students and independent learners building their first strong foundation in law.
This textbook provides an in-depth analysis on personal finance that is both practical and straightforward in its approach. It has been written in such a way that the readers can gain knowledge without getting overwhelmed by the technical terms. Suitable for both beginners and advanced learners.
All of the basic topics to get you from zero to junior pentester level - covering off everything you need to know to start breaking into web application penetration testing industry or looking for flaws on bug bounties. (LTR101)
This book gives a brief, but rigorous, treatment of statistical inference intended for practicing Data Scientists.