Название: Applications of Big Data and Artificial Intelligence in Smart Energy Systems: Volume 1
Автор: Neelu Nagpal, Hassan Haes Alhelou, Pierluigi Siano, Sanjeevikumar Padmanaban
Издательство: River Publishers
Серия: River Publishers Series in Computing and Information Science and Technology
Год: 2023
Страниц: 318
Язык: английский
Формат: pdf (true)
Размер: 10.9 MB

This book covers smart grid applications of various big data analytics, Artificial Intelligence, and Machine Learning technologies for demand prediction, decision-making processes, policy, and energy management. The book delves into new technologies such as the Internet of Things, BlockChain for smart home solutions, and smart city solutions in depth in the context of modern power systems. Implementing Big Data science for better and safer operation is possible in the context of future smart energy system’s digitization and automation. Smart plugs, switches, devices, smart grids, smart appliances, phase measurement, field measurement, RTUs, sensors mounted on grid-level equipment (e.g., transformers and network switches), asset inventory, SCADA system, geographic information system (GIS), weather data, traffic data, and social media are all expected to become massive data sources. This book covers real-time monitoring, control, and automation utilizing AI to access and extract data features. Big Data analytics is an area that has shown promising results in handling complex problems such as electricity demand forecasting. This book chapter explores the advancements in forecasting techniques of electrical demand. These advancements are explored via survey of existing literature, demonstration of techniques, and a comparative analysis of performance of Machine Learning techniques. Machine Learning techniques, viz. linear regression (LR), polynomial regression (PR), ridge regression (RR), least absolute shrinkage and selection operator (LASSO) regression, decision tree regression (DTR), random forest regression (RFR), and K nearest neighbor regression (KNNR) are demonstrated and discussed.

Название: Как быстро восстановить потерянные компьютерные данные. Подробное руководство по спасению информации
Автор: Гладкий А. А.
Издательство: ДиректМедиа
Год: 2020
Cтраниц: 291 с. : ил.
Формат: pdf (ocr)
Размер: 19 мб
Язык: русский

Внезапная потеря хранящихся в компьютере данных — это всегда драма. Особенно, если они относятся к профессиональной деятельности: можно лишиться выгодного заказа, получить крупные убытки или потерять работу. Не столь критично, но бесконечно досадно и жалко терять семейные фото и видео, коллекции фильмов и музыки, прочий любимый контент.

Название: Modern Business Analytics: Practical Data Science for Decision-making
Автор: Matt Taddy, Leslie Hendrix, Matthew C. Harding
Издательство: McGraw Hill
Год: 2023
Страниц: 465
Язык: английский
Формат: pdf (true)
Размер: 34.6 MB

Written by Matt Taddy, successful author of the McGraw Hill Professional title, Business Data Science graduate of University of Chicago and Amazon Chief Economist. This new higher-ed text takes a practical, modern approach to Data Science and business analytics for the graduate-level business analytics student or professional. It takes a learn-by-doing approach, with real data analysis examples that explain the "why", rather than the "what" in the decision-making discussions. It uses R as the primary technology throughout the text and includes an end-of-chapter reference to the basic R recipes in each chapter. The text uses tools from economics and statistics in combination with Machine Learning Techniques to create a platform for using data to make decisions. The practice of data analytics is changing and modernizing. Innovations in computation and Machine Learning are creating new opportunities for the data analyst: exposing previously unexplored data to scientific analysis, scaling tasks through automation, and allowing deeper and more accurate modeling. Spreadsheet models and pivot tables are being replaced by code scripts in languages like R and Python. There has been massive growth in digitized information, accompanied by development of systems for storage and analysis of this data. There has also been an intellectual convergence across fields - Machine Learning and Computer Science, statistics, and social sciences and economics - that has raised the breadth and quality of applied analysis everywhere. This is the Data Science approach to analytics, and it allows leaders to go deeper than ever to understand their operations, products, and customers.

Название: Mastering SQL: A Beginner's Guide
Автор: Sufyan bin Uzayr
Издательство: CRC Press
Год: 2024
Страниц: 269
Язык: английский
Формат: pdf (true), epub
Размер: 10.1 MB

Mastering SQL helps readers gain a firm understanding of the Structured Query Language. Structured Query Language, more often known as SQL, is the de facto standard language for working with databases. It is a specialized language for handling data-related tasks like creating a database, putting information into tables, modifying and extracting that information, and much more. MySQL, PostgreSQL, Oracle, SQL light, etc. are only a few examples of SQL implementations. Structured Query Language (SQL) is a query language for working with relational databases. We can use SQL to update, delete, and retrieve data from a database. A table is used to define the data/object. These tables consist of rows and columns and are uniquely identified by their field names. SQL is a fast and efficient database system. SQL allows for the rapid and efficient retrieval of huge numbers of data entries from a database. It’s a relational database. Thus, data is described in a more orderly fashion than in an unstructured database like MongoDB. Insertions, deletions, inquiries, manipulations, and computations of data through analytical queries in a relational database may all be performed in a matter of seconds.

Название: Data Analysis for the Life Sciences
Автор: Rafael A. Irizarry, Michael I. Love
Издательство: Leanpub
Год: 2021-03-17
Страниц: 511
Язык: английский
Формат: pdf (true)
Размер: 10.6 MB

In the life sciences, data analysis is now part of practically every research project. Genomics, in particular, is being driven by new measurement technologies that permit us to observe certain molecular entities for the first time. These observations are leading to discoveries analogous to identifying microorganisms and other breakthroughs permitted by the invention of the microscope. Choice examples of these technologies are microarrays and next generation sequencing. This book will cover several of the statistical concepts and data analytic skills needed to succeed in data-driven life science research. We go from relatively basic concepts related to computing p-values to advanced topics related to analyzing high-throughput data. Throughout the book we will describe visualization techniques in the statistical computer language R that are useful for exploring new data sets. For example, we will use these to learn when to apply robust statistical techniques. While statistics textbooks focus on mathematics, this book focuses on using a computer to perform data analysis. Instead of explaining the mathematics and theory, and then showing examples, we start by stating a practical data-related challenge. This book also includes the computer code that provides a solution to the problem and helps illustrate the concepts behind the solution. By running the code yourself, and seeing data generation and analysis happen live, you will get a better intuition for the concepts, the mathematics, and the theory. The book was created using the R markdown language and we make all this code available to the reader.

Название: Windows 11 For Beginners - 8th Edition, 2023
Автор: Papercut Limited
Издательство: Papercut Limited
Год: 2023
Страниц: 102
Язык: английский
Формат: pdf
Размер: 43.8 MB

"Windows 11 для новичков" - это полное руководство для неопытных пользователей настольных и портативных компьютеров, а также для тех, кто хочет узнать все необходимое для начала работы с операционной системой Microsoft. Это независимое руководство наполнено полезными советами и шаг за шагом полностью иллюстрированными инструкциями, написанными на простом и понятном английском языке. В страницах данного издания вы узнаете все, что вам нужно знать о вашем компьютере и приложениях, сначала разобравшись в операционной системе, в которой они функционируют. С этим неофициальным руководством ни одна сложность не останется неразрешенной, ни один вопрос не останется без ответа, пока вы изучаете, исследуете и улучшаете свой опыт использования Windows 11.

Название: Delta Lake: Up and Running: Modern Data Lakehouse Architectures with Delta Lake (5th Early Release)
Автор: Bennie Haelen, Dan Davis
Издательство: O’Reilly Media, Inc.
Год: 2023-07-25
Страниц: 157
Язык: английский
Формат: epub
Размер: 10.2 MB

With the rapid growth of big data and AI, organizations are quickly building data products and solutions in an ad-hoc manner. But as these data organizations mature, it's apparent that their analysis and Machine Learning (ML) models are only as reliable as the data they're built upon. The solution? Delta Lake, an open-source format that enables building a lakehouse architecture on top of existing storage systems such as S3, ADLS, and GCS. In this practical book, author Bennie Haelen shows data engineers, data scientists, and data analysts how to get Delta Lake and its unique features up and running. The ultimate goal of building data pipelines and applications is to query processed data and gain insights from it. You'll learn how the choice of storage solution determines the robustness and performance of the data pipeline, from raw data to insights. Delta Lake brings capabilities such as transactional reliability and support for UPSERTs and MERGEs to data lakes while maintaining the dynamic horizontal scalability and separation of storage and compute of data lakes. Delta Lake is one the enablers for building Data lakehouses, an open data architecture that combines the best of data warehouses and data lakes.

Название: Statistical Models and Methods for Data Science
Автор: Leonardo Grilli, Monia Lupparelli, Carla Rampichini
Издательство: Springer
Год: 2023
Страниц: 186
Язык: английский
Формат: pdf (true), epub
Размер: 18.0 MB

This book focuses on methods and models in classification and data analysis and presents real-world applications at the interface with Data Science. Numerous topics are covered, ranging from statistical inference and modelling to clustering and factorial methods, and from directional data analysis to time series analysis and small area estimation. The applications deal with new developments in a variety of fields, including medicine, finance, engineering, marketing, and cyber risk. Analyzing categorical data in Machine Learning generally requires a coding strategy. This problem is common to multivariate statistical techniques, and several approaches have been suggested in the literature. This article proposes a method for analyzing categorical variables with neural networks. Both a supervised and unsupervised approaches were considered, in which the variables can have high cardinality. Some simulated data applications illustrate the interest in the proposal.

Название: Secure Data Mining
Автор: Jocelyn O. Padallan
Издательство: Arcler Press
Год: 2022
Страниц: 244
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

Data mining is a process to extract useful knowledge from large amounts of data. To conduct data mining, we often need to collect data. However, privacy concerns may prevent people from sharing the data and some types of information about the data. How we conduct data mining without breaching data privacy presents a challenge. Secure Data Mining provides solutions to the problem of data mining without compromising data privacy. This professional book is designed for practitioners and researchers in industry, as well as a secondary textbook for advanced-level students in Computer Science. Fundamentals and basic concepts regarding data mining are given in Chapter 1 which include data types, information gained from the data, and usefulness of the data mined. Chapter 2 provides detailed knowledge about the security of the data in the process of data mining. A number of approaches of security including classification and detection of data, clustering of data, intrusion detection systems etc. are discussed in this chapter. Classification approaches of the data are discussed in Chapter 3 of this book. Categorization of data and categorization techniques, preprocessing of data and feature selection are the presented in this chapter. Chapter 4 discusses the application of secure data mining in fraud detection. This chapter gives overview of the existing fraud detection systems and compares it with the secure system of fraud detection.

Название: Data Fabric and Data Mesh Approaches with AI: A Guide to AI-based Data Cataloging, Governance, Integration, Orchestration, and Consumption
Автор: Eberhard Hechler, Maryela Weihrauch, Yan (Catherine) Wu
Издательство: Apress
Год: 2023
Страниц: 440
Язык: английский
Формат: pdf (true), epub
Размер: 41.6 MB

Understand modern data fabric and data mesh concepts using AI-based self-service data discovery and delivery capabilities, a range of intelligent data integration styles, and automated unified data governance—all designed to deliver "data as a product" within hybrid cloud landscapes. This book teaches you how to successfully deploy state-of-the-art data mesh solutions and gain a comprehensive overview on how a data fabric architecture uses Artificial Intelligence (AI) and Machine Learning (ML) for automated metadata management and self-service data discovery and consumption. You will learn how data fabric and data mesh relate to other concepts such as data DataOps, MLOps, AIDevOps, and more. Many examples are included to demonstrate how to modernize the consumption of data to enable a shopping-for-data (data as a product) experience.