The most recommended data processing books

From well-known authorities in the R-sphere (including a former R Core Team member), this is a long-standing text whose first edition was one of the early books intended to teach R to beginners. It provides concise instructions and examples on how R is used as a programming language before focusing on 'number-crunching' statistical methods that are typically seen as computationally intensive. One of the notable features of this book is the statistical methods at hand are not just illustrated using 'black-box' code--the reader is provided with the necessary mathematical detail to understand what's going on behind the scenes for those that are so inclined.

This book explores how AI is transforming healthcare and the potential benefits it can bring to patients and doctors.

The author, Eric, is a cardiologist with working knowledge of technology of AI. I love how he describes with clarity, the present and potential to make people healthier with AI First thinking. That is, how AI can make the business of health care human.

I love the premise and basis of Eric’ thinking that we can make healthcare personalized, proactive, anticipatory, helping people live healthier lives and reducing the cost of healthcare. 

At the same time he is mindful that AI could be used to dehumanize healthcare and exacerbate existing inequalities.

Like professionals in other industries, educators are recognizing the power of data and are using it to guide their decision-making. Yet quantifying what works and what doesn’t when it comes to something as variable-rich as learning is extremely difficult.

Hence, as bright as they are, educators have only a 14% accuracy rate when interpreting student data. Fortunately, authors Rees and Wynns have exactly what is needed to remedy this problem.

They offer the hard-but-important-to-look-at facts concerning data use in our schools and pair it with a clear path to fixing problems. They pull engaging stories from their extensive experience and have a whip-smart writing style I envy.

One wonders how a book on data that uncovers harsh realities can be such an enjoyable read – the kind too enthralling to put down.

This provides a superb balance between technical aspects of R coding and the statistical methods that motivate its use. It's rare to find a book on topics like this that are written with Kabacoff's easygoing yet precise style, which makes it ideal for beginners. From my own experience, it is obvious the author has spent many years teaching this type of content, knowing where things deserve extra explanation up front and where other more technical details can be relegated to more advanced texts.

Apache Kafka is the backbone of almost every streaming-based system today.

The solutions created and implemented in Kafka are the key concepts in every streaming system that you will work with.

This book will allow you to fully understand the Kafka architecture, its internals, and APIs and allow you to become an expert in this technology.

I love the fact that Ali has provided evidence that ANYONE can succeed as a founder. He has done a lot of number-crunching on ‘unicorns’ (I admire his tenacity for that!) and examined what makes a successful startup founder and some surprises emerge.

Age, education, and number of cofounders were not predictors of a startup’s success, as many of us might have expected. The big thing that does matter is experience. Sixty percent of unicorn founders had previously launched startups. It seems that in pretty much every walk of life, including this one, practice is the key.

Eldon Hall led the development of the Apollo Guidance Computer, that one-cubic-foot device with 76kb of memory that navigated, guided, and controlled each of the Apollo spacecraft — the machine that I helped program. His book is both a detailed description of the Apollo computer and a history of its development. The most dramatic chapter chronicles the bold decision to use integrated circuits in the design of the computer — all of the same type, to encourage the vendor to keep making them — although that technology was then anything but reliable. 

I love this book because it reminds us of the many ways that technology can affect justice.

It is tempting to think sophisticated tactics such as “predictive policing” can solve all problems relating to human bias. However, Brayne shows that data and algorithms do not eliminate bias and discretion. Instead, high-tech police tools simply make bias less overt and visible, which erodes the public’s ability to hold the police accountable.

I especially enjoyed how the book flips the script, considering diverse ways to use these tools to help the public. For example, how can municipalities use technology to analyze the underlying factors that contribute to policing problems in the first place?

If I were getting started with coding graphics today, I would start with this book, hands down. Learning p5 is the easiest way to create interactive graphics that run in a web browser, and this book is a very friendly, accessible, and beautifully illustrated introduction to coding graphics with p5.js—no prior experience needed. You might be wondering about the name “p5.js”. It’s a JavaScript library (that’s the “.js” part) based on Processing, the open-source programming language created for artists and designers. (More on Processing in a moment.) I have taught college courses with this book, and students love it. Plus, all the skills you learn here with p5 are applicable to JavaScript—the world’s most popular programming language—more generally.

Books on AI often go to extremes, either promoting it as the solution to all the world’s problems, or depicting it as an evil that will destroy humanity.

This book is much more practical, and based on experience using AI in actual business applications. It is the result of considerable research, involving investigation of applications not only in silicon-valley, but from various business sectors, such as Airbus, Ping, Progressive Insurance, and Capital One Bank.

Don’t let the title fool you; this book is not simply a promotion of AI, but addresses the practical issues that have to be considered if success is to be achieved. For example, they argue that “the most important aspect in AI success is not machinery, but human leadership, behavior, and change.”