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…
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