Statistics with Julia: Fundamentals for Data Science, Machine Learning and Artificial Intelligence

This book is a comprehensive guide to probability and statistics using the Julia language, designed for practitioners and researchers in data science, machine learning, bio-statistics, finance, or engineering. It covers basic concepts, distributions, inference, regression analysis, machine learning methods, and Monte Carlo simulation, with over 200 code examples and downloadable Julia code.

Format: Paperback / softback
Length: 527 pages
Publication date: 05 September 2022
Publisher: Springer Nature Switzerland AG

This comprehensive monograph employs the Julia language to facilitate a thorough exploration of probability and statistics, with the ultimate goal of mastering machine learning, data science, and artificial intelligence. The text assumes a fundamental understanding of programming and mathematical notation and does not delve into prior statistical knowledge. It is designed to be accessible to practitioners and researchers in diverse fields such as data science, machine learning, bio-statistics, finance, and engineering who seek to strengthen their grasp of probability and statistics.

The book is structured into ten independent chapters, beginning with an introduction to the Julia programming language. It then proceeds to cover basic probability concepts, distributions, statistical inference, regression analysis, machine learning methods, and the application of Monte Carlo simulation for dynamic stochastic models. Throughout the text, over 200 code examples are provided to illustrate numerous key statistical concepts, making it an invaluable resource for both beginners and experienced practitioners.

The Julia code is written in a simple and concise format, with parameters that can be easily modified. It is available for download from the book's associated GitHub repository, allowing readers to experiment with the code and gain a deeper understanding of statistical concepts.

Co-creators of the Julia language, Professor Alan Edelman from MIT and Dr. Viral Shah from Julia Computing, have expressed their high praise for "Statistics with Julia." Professor Edelman describes the book as an easy-to-read, well-organized, and modern introduction to statistics, highlighting its ability to be understood both through static page reading and live computer execution. Dr. Shah emphasizes the book's modern approach to learning statistics, stating that it provides a comprehensive and self-contained reference for those seeking to delve into the field.

In conclusion, "Statistics with Julia" is a highly recommended resource for anyone interested in mastering probability and statistics, particularly those working in data science, machine learning, bio-statistics, finance, or engineering. Its comprehensive coverage, accessible language, and extensive code examples make it an invaluable tool for both beginners and experienced practitioners alike. Whether you are seeking to expand your statistical knowledge or apply it in practical applications, this monograph will undoubtedly be a valuable asset in your journey.

Weight: 1316g
Dimension: 279 x 210 (mm)
ISBN-13: 9783030709037
Edition number: 1st ed. 2021