Free Download Data Stewardship in Action
by Lee, Pui Shing;Charm, Toa;
English | 2024 | ISBN: 1837636591 | 272 pages | True PDF | 17.93 MB

Free Download Data Science of Renewable Energy Integration: The Nexus of Energy, Environment, and Economic Growth
English | 2024 | ISBN: 9819987784 | 342 Pages | PDF EPUB (True) | 39 MB
This book covers various data scientific approaches to analyze the issue of grid integration of renewable energy for which the grid flexibility is the key to cope with its intermittency. It provides readers with the scope to view renewable energy integration as establishing a distributed energy network instead of the traditional centralized energy system. Specifically, quantitative valuation system-wise of the levelized cost of energy, which includes both initial cost and various operational costs, enables readers to optimize energy systems in order to minimize economic cost and environmental impact. It is noted, however, that the high cost of integrating renewable energy on a large scale might slow economic growth considerably. Topics addressed in the book also include statistical comparative study of the relationship between energy and economic growth, a graphical model of determinant factors for foreign direct investment in renewable energy, the coupled oscillator model and unit commitment model to capture intermittency of renewable energy, and the network model of evolving micro-grids. The book explains desired innovation to reduce the integration cost significantly using innovative technologies such as energy storage with hydrogen production and vehicle-to-grid technology. Illustrated by careful analysis of selected examples of renewable integration using different types of grid flexibility, this volume is indispensable to readers who make policy recommendations to establish the distributed energy network integrated with large-scale renewable energy by disentangling the nexus of energy, environment, and economic growth.

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English | 2024 | ISBN: 9819978610 | 591 Pages | PDF EPUB (True) | 68 MB
This book gathers outstanding papers presented at the International Conference on Data Science and Applications (ICDSA 2023), organized by Soft Computing Research Society (SCRS) and Malaviya National Institute of Technology Jaipur, India, from 14 to 15 July 2023. The book is divided into four volumes, and it covers theoretical and empirical developments in various areas of big data analytics, big data technologies, decision tree learning, wireless communication, wireless sensor networking, bioinformatics and systems, artificial neural networks, deep learning, genetic algorithms, data mining, fuzzy logic, optimization algorithms, image processing, computational intelligence in civil engineering, and creative computing.

Free Download Data Mining for Co-location Patterns: Principles and Applications
English | 2022 | ISBN: 0367654261 | 317 Pages | EPUB (True) | 11 MB
Co-location pattern mining detects sets of features frequently located in close proximity to each other. This book focuses on data mining for co-location pattern, a valid method for identifying patterns from all types of data and applying them in business intelligence and analytics. It explains the fundamentals of co-location pattern mining, co-location decision tree, and maximal instance co-location pattern mining along with an in-depth overview of data mining, machine learning, and statistics. This arrangement of chapters helps readers understand the methods of co-location pattern mining step-by-step and their applications in pavement management, image classification, geospatial buffer analysis, etc.

Free Download Data Management Solutions Using SAS Hash Table Operations: A Business Intelligence Case Study By Paul Dorfman; Don Henderson
2018 | 400 Pages | ISBN: 1629601438 | PDF | 6 MB
Hash tables can do a lot more than you might think! Data Management Solutions Using SAS® Hash Table Operations: A Business Intelligence Case Study concentrates on solving your challenging data management and analysis problems via the power of the SAS hash object, whose environment and tools make it possible to create complete dynamic solutions. To this end, this book provides an in-depth overview of the hash table as an in-memory database with the CRUD (Create, Retrieve, Update, Delete) cycle rendered by the hash object tools. By using this concept and focusing on real-world problems exemplified by sports data sets and statistics, this book seeks to help you take advantage of the hash object productively, in particular, but not limited to, the following tasks: select proper hash tools to perform hash table operations use proper hash table operations to support specific data management tasks use the dynamic, run-time nature of hash object programming understand the algorithmic principles behind hash table data look-up, retrieval, and aggregation learn how to perform data aggregation, for which the hash object is exceptionally well suited manage the hash table memory footprint, especially when processing big data use hash object techniques for other data processing tasks, such as filtering, combining, splitting, sorting, and unduplicating. Using this book, you will be able to answer your toughest questions quickly and in the most efficient way possible!

Free Download Data Cleaning with Power BI: The definitive guide to transforming dirty data into actionable insights
English | 2024 | ISBN: 1805126407 | 340 Pages | EPUB | 19 MB
This book serves as a comprehensive guide to data cleaning, starting with data quality, common data challenges, and best practices for handling data. You'll learn how to import and clean data with Query Editor and transform data using the M query language. As you advance, you'll explore Power BI's data modeling capabilities for efficient cleaning and establishing relationships. Later chapters cover best practices for using Power Automate for data cleaning and task automation. Finally, you'll discover how OpenAI and ChatGPT can make data cleaning in Power BI easier.

Free Download Data Analytics and Learning: Proceedings of DAL 2022
English | 2024 | ISBN: 9819963451 | 265 Pages | PDF EPUB (True) | 62 MB
This book presents new theories and working models in the areas of data analytics and learning. The papers included in this volume were presented at the second International Conference on Data Analytics and Learning (DAL 2022), which was organized by the Department of Computer Science & Engineering, Alva's Institute of Engineering & Technology, Moodbidri, Mangalore, Karnataka, India in association with the Department of Studies in Computer Science, University of Mysore, Mysuru, Karnataka, India. The areas covered include pattern recognition, image processing, deep learning, computer vision, data analytics, machine learning, artificial intelligence, and intelligent systems.

Free Download Cracking the Data Science Interview: Unlock insider tips from industry experts to master the data science field
English | 2024 | ISBN: 1805120506 | 404 Pages | EPUB (True) | 10 MB
The data science job market is saturated with professionals of all backgrounds, including academics, researchers, bootcampers, and Massive Open Online Course (MOOC) graduates. This poses a challenge for companies seeking the best person to fill their roles. At the heart of this selection process is the data science interview, a crucial juncture that determines the best fit for both the candidate and the company.

Free Download Cody's Data Cleaning Techniques Using SAS By Ron Cody
2017 | 210 Pages | ISBN: 1629607967 | PDF | 19 MB
Written in Ron Cody's signature informal, tutorial style, this book develops and demonstrates data cleaning programs and macros that you can use as written or modify which will make your job of data cleaning easier, faster, and more efficient. --

Free Download Frederic Magoules, Jie Pan, Fei Teng, "Cloud Computing: Data-Intensive Computing and Scheduling"
English | 2019 | pages: 230 | ISBN: 0367380846, 1466507829 | PDF | 6,2 mb
As more and more data is generated at a faster-than-ever rate, processing large volumes of data is becoming a challenge for data analysis software. Addressing performance issues, Cloud Computing: Data-Intensive Computing and Scheduling explores the evolution of classical techniques and describes completely new methods and innovative algorithms. The book delineates many concepts, models, methods, algorithms, and software used in cloud computing.