Название: Advances in Data Science and Artificial Intelligence
Автор: Rajiv Misra, Nishtha Kesswani, Muttukrishnan Rajarajan, Bharadwaj Veeravalli
Издательство: Springer
Год: 2023
Страниц: 521
Язык: английский
Формат: pdf (true)
Размер: 15.0 MB

With the intriguing development of technologies in several industries along with the advent of accrescent and ubiquitous computational resources, it creates an ample number of opportunities to develop innovative intelligence technologies in order to solve the wide range of uncertainties, imprecision, and vagueness issues in various real-life problems. Hybridizing modern Computational Intelligence with traditional computing methods has attracted researchers and academicians to focus on developing innovative AI techniques using Data Science. International Conference on Data Science and Artificial Intelligence (ICDSAI) 2022, organized on April 23-24, 2022 by the Indian Institute of Technology, Patna at NITIE Mumbai (India) in collaboration with the International Association of Academicians (IAASSE) USA collected scientific and technical contributions with respect to models, tools, technologies, and applications in the field of modern Artificial Intelligence and Data Science, covering the entire range of concepts from theory to practice, including case studies, works-in-progress, and conceptual explorations. The main conference included over four technical sections that focused on fundamentals of Data Science applications in mechanical engineering, ML and Artificial Intelligence (AI), BOT, Web development, app development.

Название: Data Science with Semantic Technologies: Deployment and Exploration
Автор: Archana Patel, Narayan C. Debnath
Издательство: CRC Press
Год: 2023
Страниц: 246
Язык: английский
Формат: pdf (true)
Размер: 13.2 MB

Gone are the days when data was interlinked with related data by humans and human interpretation was required. Data is no longer just data. It is now considered a Thing or Entity or Concept with meaning, so that a machine not only understands the concept but also extrapolates the way humans do. Data Science with Semantic Technologies: Deployment and Exploration, the second volume of a two-volume handbook set, provides a roadmap for the deployment of semantic technologies in the field of Data Science and enables the user to create intelligence through these technologies by exploring the opportunities and eradicating the challenges in the current and future time frame. In addition, this book offers the answer to various questions like: What makes a technology semantic as opposed to other approaches to Data Science? What is knowledge data science? How does knowledge data science relate to other fields? This book explores the optimal use of these technologies to provide the highest benefit to the user under one comprehensive source and title.

Название: Learn Hadoop in 24 Hours
Автор: Alex Nordeen
Издательство: Independently published
Год: 2021
Страниц: 188
Язык: английский
Формат: pdf, epub
Размер: 10.2 MB

Hadoop has changed the way large data sets are analyzed, stored, transferred, and processed. At such low cost, it provides benefits like supports partial failure, fault tolerance, consistency, scalability, flexible schema, and so on. It also supports cloud computing. More and more number of individuals are looking forward to mastering their Hadoop skills. While initiating with Hadoop, most users are unsure about how to proceed with Hadoop. They are not aware of what are the pre-requisite or data structure they should be familiar with. Or How to make the most efficient use of Hadoop and its ecosystem. To help them with all these queries and other issues this e-book is designed. The book gives insights into many of Hadoop libraries and packages that are not known to many Big data Analysts and Architects.

Название: Modern Vulnerability Management: Predictive Cybersecurity
Автор: Michael Roytman, Ed Bellis
Издательство: Artech House
Год: 2023
Страниц: 237
Язык: английский
Формат: pdf (true)
Размер: 13.9 MB

This book comprehensively covers the principles of Risk-based vulnerability management (RBVM) – one of the most challenging tasks in cybersecurity -- from the foundational mathematical models to building your own decision engine to identify, mitigate, and eventually forecast the vulnerabilities that pose the greatest threat to your organization. You will learn: how to structure data pipelines in security and derive and measure value from them; where to procure open-source data to better your organization’s pipeline and how to structure it; how to build a predictive model using vulnerability data; how to measure the return on investment a model in security can yield; which organizational structures and policies work best, and how to use Data Science to detect when they are not working in security; and ways to manage organizational change around Data Science implementation. Using the many sources of data we have and the mathematical modeling we use to compensate for mathematical scale, randomness, and uncertainty, Machine Learning (ML) offers a quick and efficient way to better prioritize decisions and remediate the vulnerabilities that pose the greatest risk. ML is a classification of Artificial Intelligence in which algorithms automatically improve over time by observing patterns in data and applying those patterns to subsequent actions.

Название: Streaming Data Mesh: A Model for Optimizing Real-Time Data Services (Final Release)
Автор: Hubert Dulay, Stephen Mooney
Издательство: O’Reilly Media, Inc.
Год: 2023
Страниц: 223
Язык: английский
Формат: epub
Размер: 10.2 MB

Data lakes and warehouses have become increasingly fragile, costly, and difficult to maintain as data gets bigger and moves faster. Data meshes can help your organization decentralize data, giving ownership back to the engineers who produced it. This book provides a concise yet comprehensive overview of data mesh patterns for streaming and real-time data services. Data mesh is one of the most popular architectures for data platforms that many are exploring today. This book will help you get a full understanding of this self-servicing data platform in a streaming context. Today, batch processing dominates all extract, transform, and load (ETL) processes in most businesses. This book will help show a different perspective of data pipelines and apply the same concepts you already understand in batch ETL, but in a streaming ETL in the context of a data mesh. This book is designed to help you understand the essential concepts around streaming data mesh—the concepts, architectures, and technologies at its core.

Название: Getting Started with Big Data Query using Apache Impala
Автор: Agus Kurniawan
Издательство: PE Press
Год: 2021
Страниц: 120
Язык: английский
Формат: pdf, epub
Размер: 15.5 MB

This book provides alternative approach to get started with Big Data Query using Apache Impala. This book describes how to work with Apache Impala and to perform queries inside Apache Impala. Apache Impala is a modern, open source, distributed SQL query engine for Apache Hadoop. With Impala, we can query data, whether stored in HDFS, Apache Hive or Apache HBase – including SELECT, JOIN, and aggregate functions. You can find the official project on this link, In this book, we learn how to perform queries on Apache Impala. Apache Hue is a web tool that can be used to perform queries on Apache Impala. We can say Apache Hue like MySQL Workbench in MySQL or SQL Server Management Studio in SQL Server. We can use Apache Hue to write queries to Apache Impala easily. In this chapter, we learn how to access Apache Impala from a program. We will use Java application for a sample of client application. To access Apache Impala, we can use ODCB and JDBC drivers from Cloudera. We will JDBC 4.2 driver for Java application. Next, we create Java application project.

Название: Data Science for Complex Systems
Автор: Anindya S. Chakrabarti, K. Shuvo Bakar, Anirban Chakraborti
Издательство: Cambridge University Press
Год: 2023
Страниц: 305
Язык: английский
Формат: pdf
Размер: 19.0 MB

Many real-life systems are dynamic, evolving, and intertwined. Examples of such systems displaying 'complexity', can be found in a wide variety of contexts ranging from economics to biology, to the environmental and physical sciences. The study of complex systems involves analysis and interpretation of vast quantities of data, which necessitates the application of many classical and modern tools and techniques from statistics, network science, Machine Learning, and agent-based modelling. Drawing from the latest research, this self-contained and pedagogical text describes some of the most important and widely used methods, emphasising both empirical and theoretical approaches. More broadly, this book provides an accessible guide to a data-driven toolkit for scientists, engineers, and social scientists who require effective analysis of large quantities of data, whether that be related to social networks, financial markets, economies or other types of complex systems.

Название: Resilient Oracle PL/SQL: Building Resilient Database Solutions for Continuous Operation (Final Release)
Автор: Stephen B. Morris
Издательство: O’Reilly Media, Inc.
Год: 2023
Страниц: 305
Язык: английский
Формат: epub (true)
Размер: 10.2 MB

As legacy and other critical systems continue to migrate online, the need for continuous operation is imperative. Code has to handle data issues as well as hard external problems today, including outages of networks, storage systems, power, and ancillary systems. This practical guide provides system administrators, DevSecOps engineers, and cloud architects with a concise yet comprehensive overview on how to use PL/SQL to develop resilient database solutions. If you’re interested in learning something about databases and PL/SQL, this book is a good place to start. It takes a first-principles approach, so not much foundational knowledge is required. The focus is on a good practice in PL/SQL, and the use of requirements analysis and metrics should be helpful to readers of all technical levels.

Название: Basic Computational Techniques for Data Analysis: An Exploration in MS Excel, 2nd Edition
Автор: D. Narayana, Sharad Ranjan, Nupur Tyagi
Издательство: Routledge
Год: 2023
Страниц: 301
Язык: английский
Формат: pdf (true)
Размер: 23.7 MB

This book is designed to equip students to navigate through MS Excel and basic data computation methods, which are essential tools in research or professional settings and in classrooms. It illustrates the concepts used in research and data analysis and economic and financial decision-making in business and in daily life. The book will help students acquire knowledge and develop skills in statistical techniques and financial analysis using MS Excel. The book is developed through three phases, with each phase standing on its own as well as providing a foundation for the next. In the first phase, Excel is introduced for the students to learn entry of data, manipulation of data, carrying out operations and develop presentations. The second phase introduces basic statistical measures of data summarisation and analysis, following which these are illustrated in Excel spreadsheets with the techniques introduced in the first phase. In addition, a few advanced tools of statistical analysis are introduced and illustrated in Excel. The third phase introduces financial measures of common use, their general computation and working them out in Excel.

Название: Applied Data Science: Data Translators Across the Disciplines
Автор: Douglas G. Woolford, Donna Kotsopoulos, Boba Samuels
Издательство: Springer
Серия: Studies in Big Data
Год: 2023
Страниц: 195
Язык: английский
Формат: pdf (true), epub
Размер: 32.0 MB

The use of data to guide action is growing. Even the public uses data to guide everyday decisions! How do we develop data acumen across a broad range of fields and varying levels of expertise? How do we foster the development of effective data translators? This book explores these questions, presenting an interdisciplinary collection of edited contributions across fields such as education, health sciences, natural sciences, politics, economics, business and management studies, social sciences, and humanities. Authors illustrate how to use data within a discipline, including visualization and analysis, translating and communicating results, and pedagogical considerations. This book is of interest to scholars and anyone looking to understand the use of Data Science across disciplines. It is ideal in a course for non-data science majors exploring how data translation occurs in various contexts and for professionals looking to engage in roles requiring data translation.