Author Description

Product Description It has never been easier for organizations to gather, store, and process data. Use of data science is driven by the rise of big data and social media, the development of high-performance computing, and the emergence of such powerful methods for data analysis and modeling as deep learning. Data science encompasses a set of principles, problem definitions, algorithms, and processes for extracting non-obvious and useful patterns from large datasets. It is closely related to the fields of data mining and machine learning, but broader in scope. This book offers a brief history of the field, introduces fundamental data concepts, and describes the stages in a data science project. It considers data infrastructure and the challenges posed by integrating data from multiple sources, introduces the basics of machine learning, and discusses how to link machine learning expertise with real-world problems. The book also reviews ethical and legal issues, developments in data regulation, and computational approaches to preserving privacy. Finally, it considers the future impact of data science and offers principles for success in data science projects. About the Author John D. Kelleher is Academic Leader of the Information, Communication, and Entertainment Research Institute at the Technological University Dublin. He is coauthor of Data Science and Fundamentals of Machine Learning for Predictive Data Analytics. Brendan Tierney, Oracle ACE Director, is an independent consultant and lectures on data mining and advanced databases in the Dublin Institute of Technology in Ireland. Chris Sorensen is a veteran audiobook narrator with over 160 titles to his name. He has received three AudioFile Earphones Awards, and his recording of Sent by Margaret Peterson Haddix was selected as one of the Best Audiobooks of 2010 by AudioFile magazine. He is a member of SAG-AFTRA and the APA.