Carrone, F., Nicolini, M., & Obst Demaestri, H. (2021). Data Science in Julia for Hackers. Retrieved March, 2024, from https://datasciencejuliahackers.com/
One of the first things to note about this book is that it is not an academic textbook. The authors of this book are not academics but a multidisciplinary team of passionate, amateur practitioners from different backgrounds, namely Engineering, Computer Science, Physics and Economy, that found a common ground to write this book, and that day by day keep reading, learning and applying new approaches, technologies and ways of thinking. This book lies somewhere in between a methodological recipe and a theoretical intensive textbook. What we want to deliver is a mathematical and computational methodology to face concrete Data Science problems, that is, applying theory and science to real-world problems involving data. The relationship between theory and practice is complex. Considering them as a whole can take us much farther. These pages may offer the theorist a way to think about problematic situations in a more down to earth manner, and to the practitioner, stimulation to go beyond the mere application of programming libraries and tools.
As the name of the book states, this is a book for Hackers. The term can have opposite connotations, depending on who is pronouncing it and to whom it refers to. In media and pop culture, it is associated with cyber-criminals, people that use computers and technology with malicious intent. In the cyber-security domain, hackers are, as stated in the final chapter of Hacking: The Art of Exploitation by Jon Erickson, “…just people with innovative spirits and an in-depth knowledge of technology”. But the definition we like the most is borrowed from The Jargon File’s glossary, written by Eric S. Raymond, > “A person who delights in having an intimate understanding of the internal workings of a system, computers and computer networks in particular.”
It is in this sense that this book is meant for hackers: it will lead you down a road with a results-driven perspective, slowly growing intuition about the inner workings of many problems involving data and what they all have in common, with an emphasis on application. The name of the book is also inspired by the great Bayesian Methods for Hackers, which had a big influence on the topics and the approach of this book.
One of the first things to note about this book is that it is not an academic textbook. The authors of this book are not academics but a multidisciplinary team of passionate, amateur practitioners from different backgrounds, namely Engineering, Computer Science, Physics and Economy, that found a common ground to write this book, and that day by day keep reading, learning and applying new approaches, technologies and ways of thinking. This book lies somewhere in between a methodological recipe and a theoretical intensive textbook. What we want to deliver is a mathematical and computational methodology to face concrete Data Science problems, that is, applying theory and science to real-world problems involving data. The relationship between theory and practice is complex. Considering them as a whole can take us much farther. These pages may offer the theorist a way to think about problematic situations in a more down to earth manner, and to the practitioner, stimulation to go beyond the mere application of programming libraries and tools.
As the name of the book states, this is a book for Hackers. The term can have opposite connotations, depending on who is pronouncing it and to whom it refers to. In media and pop culture, it is associated with cyber-criminals, people that use computers and technology with malicious intent. In the cyber-security domain, hackers are, as stated in the final chapter of Hacking: The Art of Exploitation by Jon Erickson, “…just people with innovative spirits and an in-depth knowledge of technology”. But the definition we like the most is borrowed from The Jargon File’s glossary, written by Eric S. Raymond, > “A person who delights in having an intimate understanding of the internal workings of a system, computers and computer networks in particular.”
It is in this sense that this book is meant for hackers: it will lead you down a road with a results-driven perspective, slowly growing intuition about the inner workings of many problems involving data and what they all have in common, with an emphasis on application. The name of the book is also inspired by the great Bayesian Methods for Hackers, which had a big influence on the topics and the approach of this book.
