Applied Modeling Techniques and Data Analysis 1: Computational Data Analysis Methods and Tools

Data analysis is a growing field that has seen rapid growth in the tech industry and the wide applicability of computational techniques. Modeling enables data analysts to identify relationships, make predictions, and understand and visualize the extracted information more strategically. Applied Modeling Techniques and Data Analysis 1 is a collective work by leading scientists, analysts, engineers, mathematicians, and statisticians that covers a cross-section of current concerns and research interests in the above scientific areas.

Format: Hardback
Length: 304 pages
Publication date: 11 May 2021
Publisher: ISTE Ltd

Big data, artificial intelligence, and data analysis have seen significant growth in recent years, driven by technological advancements and the widespread application of computational techniques. This field encompasses the scientific exploration and interpretation of large datasets, leveraging advanced analytical tools and modeling techniques to extract valuable insights. Applied Modeling Techniques and Data Analysis 1, a collaborative effort by renowned scientists, analysts, engineers, mathematicians, and statisticians, presents the latest developments in this area. The book covers a wide range of current concerns and research interests within big data, artificial intelligence, and data analysis, providing both theoretical and applied information on data analysis methods, models, and techniques.

The chapters in this book are organized into relevant sections, allowing readers to gain a comprehensive understanding of data analysis methodologies, models, and applications. The material is presented in a clear and concise manner, making it accessible to a broad audience, including researchers, practitioners, and students interested in these fields.

One of the key strengths of Applied Modeling Techniques and Data Analysis 1 is its interdisciplinary approach. The book brings together experts from various scientific and technical backgrounds, fostering collaboration and knowledge exchange. This collaboration ensures that the latest research findings and best practices are incorporated into the book, providing readers with a comprehensive and up-to-date understanding of the latest developments in big data, artificial intelligence, and data analysis.

In conclusion, Applied Modeling Techniques and Data Analysis 1 is a valuable resource for anyone interested in big data, artificial intelligence, and data analysis. The book offers a comprehensive and up-to-date overview of the latest developments in this field, providing readers with both theoretical and applied information on data analysis methods, models, and techniques. With its interdisciplinary approach and collaboration between experts, the book is sure to be a valuable tool for researchers, practitioners, and students alike.

Weight: 574g
Dimension: 262 x 163 x 21 (mm)
ISBN-13: 9781786306739