This is a book for people who want to learn about the Julia language with a view to using it for data science. Some effort has gone into making this book suitable for someone who has familiarity with the R software and wants to learn about Julia. However, prior knowledge of R is not a requirement. While this book is not intended as a textbook for a course, some may find it a useful book to follow for a course that introduces statistics or data science students to Julia. It is our sincere hope that students, researchers and data scientists in general, who wish to learn Julia, will find this book beneficial.
This book is not intended as an exhaustive introduction to data science. In fact, this book is far from an exhaustive introduction to data science. There are many very good books that one can consult to learn about different aspects of data science, but this book is primarily about Julia. Nevertheless, several important topics in data science are covered. These include data visualization, supervised learning, and unsupervised learning. When discussing supervised learning, we place some focus on gradient boosting a machine learning technique because we have found this approach very effective in applications. However, for unsupervised learning, we take a more statistical approach and place some focus on the use of probabilistic principal components analysers and a mixture thereof.
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T. Judgi, N. Srinivasan, A. Pravin, T. Prem Jacob
Dr. T. Judgi received B.Tech degree in Information Technology from Jayaram College of Engineering and Technology, Anna University, M.E degree in Computer Science and Engineering, Veltech Engineering College, Anna University and Ph.D degree from Madras Institute of Science and Technology, Anna University, Chennai, India. She works currently as an Associate Professor of Computer Science and Engineering in Sathyabama Institute of Science and Technology, Chennai. She has more than 10 Years of academic experience. she has participated and presented many Research Papers in International and National Conferences. She has published more than 15 reputed Journals and Conferences. The area of interests includes Cloud computing, Cyber Security Data Mining, Data Science.
Dr. N. Srinivasan, is currently working as an Associate Professor, Department of Computer Science Engineering, School of Computing, Sathyabama Institute of Science and Technology, Chennai, India, the institute that is well known for higher education, research and innovation. He is an active researcher and a teacher with an experience of twenty plus years. His field of interest includes prediction, soft computing and stock market. He had published many papers in various journals and conferences. He is an active member of various professional organizations.
Dr. A. Pravin received the B.E degree in Computer Science and Engineering from Bharath Niketan Engineering College, Madurai Kamaraj University, Madurai, India in 2003, M.E degree in Computer Science and Engineering from Sathyabama University, Chennai, India in 2005 and Ph.D. degree in Computer Science & Engineering at Sathyabama University, Chennai, India in 2014. He works currently as an Associate Professor for the Department of Computer Science and Engineering at Sathyabama Institute of Science and Technology, Chennai and he has 17 Years of teaching experience.
Dr. T. Prem Jacob received the B.E degree in Computer Science and Engineering from C.S.I Institute of Technology, Manonmaniam Sundaranar University, Nagercoil, India in 2004, M.E degree in Computer Science and Engineering from Sathyabama University, Chennai, Indian 2006 and Ph.D. degree from Sathyabama University, Chennai, India. He works currently as an Associate Professor of Computer Science and Engineering in Sathyabama Institute of Science and Technology Chennai. He has participated and presented many Research Papers in International and National Conferences.
