I am a professional software developer with an interest in biostatistics. I picked up this book to gain a deeper understanding of Kaplan-Meier graphs and accompanying theories around them. This book went into many more details than I found accessible. Nonetheless, it introduced me to hazard plots and hazard analysis – a concept that I was able to apply to my work. Mathematics/statistics and R code are used heavily in this book. To garner the…
Professionally, I write software used for data collection in biomedical research projects. My current project extends from data collection into the field of interpretation. Combining these demands requires that I learn something about data cleaning. Thus, this book’s title caught my eye. It is an academic book, not a popular book. I usually write in-depth book reviews on what I read, so I am writing one here. This book seems like it began as an…
First, let me define the lay of the land for the curious reader. Biostatistics is the study of statistics relevant for biomedical applications. It combines mathematics and the bio world, which includes Public Health and Epidemiology. R is free software for a programming environment that allows researchers to perform advanced analyses of statistical questions on datasets. This volume by Chan was the first textbook that addressed R and biostatistics in depth in the same volume.…
The conscientious reader should carefully heed the words of this title. The book functions as an introduction to Python that leads, step by step, to using it with Machine Learning. It takes the shortest and easiest path to get there. As such, it provides fairly immediate gratification for the reader. With such low-hanging fruit, its intended audience is beginners without a lot of knowledge in computer science. For that audience, Anis effectively communicates his message.…
by Michael WalkerCopyright (c) 2018. This book sits in a series by the publishing house AI Sciences that traverses topics in the field of Artificial Intelligence to make these subjects more accessible for the masses. I bought this book’s Kindle Edition for only $5. Interestingly, this was one of the most expensive items in the series. I am glad to have taken this short (77-page) book for a perusal. It reviewed some of my prior…
Data Science by John D. Kelleher and Brendan Tierney Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples, and Case Studies by John D. Kelleher, Brian MacNamee and Aoife D’Arcy
R for Data Scienceby Hadley Wickham and Garret Grolemund.(c) 2017. If the above quote is the mission of this book, consider the task accomplished. Where most books in computer science fall down in trying to be cute while communicating an educational message, this book addresses the task of education about R squarely, and it does so in a manner that engages the mind with interesting problems. Usually, I skip the exercises sections of most computer…