Introduction¶
Preface¶
The Data-Driven Science TextBook contains the reference material for the Data-Driven Science Lectures given at the De Vinci Innovation Center.
Data-Driven Science is an inter-disciplinary field of Computer Science using scientific processes to extract knowledge from structured or unstructured data. The field concentrates on multiple hot science subfields such as Big Data, Data Visualization, Data Sonification, Data Mining, Machine Learning, Deep Learning and more.
The fundamental sciences of Linear Algebra, Statistics and Probabilities, Optimization, and Algorithmy are essential to the Data-Driven Sciences. This book does not aim at covering all of those fields in detail. It provides enough material to build interest for students in the Data-Driven Science fields. In this sense, each chapter introduces the mathematical knowledge necessary to apply it to real-world applications.
Python 3.8 is chosen as the reference language in this book as it is for the moment one of the programming language of choice for Data Science, along with standard libraries such as Numpy, Matplotlib, and PyTorch. Each subject discussed throughout the chapters comes with direct implementation examples.
Author Biography¶
Yliess HATI is a Ph.D. student at the De Vinci Innovation Center (DVIC), the trans-disciplinary research lab of the Pôle Universitaire Léonard de Vinci Paris - La Défense. He is graduated from the engineering school ESILV in Computer Science. His research focuses on the field of Deep Learning (DL) and, more particularly, on its use for Human-Computer Interaction (HCI) by creating interactive new experiences. He has published in academic research conferences such as the International Conference on Auditory Display and ACM SIGGRAPH European Conference on Visual Media Production.