BOOKS - Supervised and Unsupervised Data Engineering for Multimedia Data
Supervised and Unsupervised Data Engineering for Multimedia Data - Suman Kumar Swarnkar, J.P. Patra, Sapna Singh Kshatri 2024 PDF | EPUB Wiley-Scrivener BOOKS
ECO~15 kg CO²

1 TON

Views
76298

Telegram
 
Supervised and Unsupervised Data Engineering for Multimedia Data
Author: Suman Kumar Swarnkar, J.P. Patra, Sapna Singh Kshatri
Year: 2024
Pages: 372
Format: PDF | EPUB
File size: 10.1 MB
Language: ENG



Pay with Telegram STARS
Supervised and Unsupervised Data Engineering for Multimedia Data In today's world, technology is advancing at an unprecedented rate, and it is essential to understand the process of its evolution to ensure the survival of humanity and unity among nations. The book "Supervised and Unsupervised Data Engineering for Multimedia Data" provides a comprehensive overview of the development of data engineering techniques for multimedia data, highlighting their potential applications and challenges. This book is a valuable resource for researchers, practitioners, and students who want to learn about the latest trends in data engineering and their practical applications. The book begins by discussing the importance of understanding the evolution of technology and its impact on society. It emphasizes the need to develop a personal paradigm for perceiving the technological process of developing modern knowledge as the basis for survival. This chapter sets the stage for the rest of the book, providing readers with a solid foundation for understanding the concepts that follow. Chapter 1: Introduction to Data Engineering This chapter introduces the concept of data engineering and its significance in today's digital age.
Контролируемая и неконтролируемая инженерия данных для мультимедийных данных В современном мире технологии развиваются с беспрецедентной скоростью, и важно понимать процесс их эволюции, чтобы обеспечить выживание человечества и единство между нациями. В книге «Supervised and Unsupervised Data Engineering for Multimedia Data» (Контролируемая и неконтролируемая инженерия данных для мультимедийных данных) представлен всесторонний обзор разработки методов инженерии данных для мультимедийных данных с выделением их потенциальных применений и проблем. Эта книга является ценным ресурсом для исследователей, практиков и студентов, которые хотят узнать о последних тенденциях в области инженерии данных и их практических применениях. Книга начинается с обсуждения важности понимания эволюции технологий и их влияния на общество. В нем подчеркивается необходимость выработки личностной парадигмы восприятия технологического процесса развития современных знаний как основы выживания. Эта глава закладывает основу для остальной части книги, предоставляя читателям прочную основу для понимания следующих концепций. Глава 1: Введение в Data Engineering В этой главе представлена концепция Data Engineering и ее значение в современную цифровую эпоху.
Ingénierie de données contrôlées et non contrôlées pour les données multimédia Dans le monde d'aujourd'hui, les technologies évoluent à une vitesse sans précédent et il est important de comprendre leur processus d'évolution pour assurer la survie de l'humanité et l'unité entre les nations. livre « Supervised and Unsupervised Data Engineering for Multimedia Data » donne un aperçu complet du développement des techniques d'ingénierie des données pour les données multimédia, en soulignant leurs applications et leurs problèmes potentiels. Ce livre est une ressource précieuse pour les chercheurs, les praticiens et les étudiants qui souhaitent en apprendre davantage sur les dernières tendances en ingénierie des données et leurs applications pratiques. livre commence par discuter de l'importance de comprendre l'évolution des technologies et leur impact sur la société. Il souligne la nécessité d'élaborer un paradigme personnel pour la perception du processus technologique du développement des connaissances modernes comme base de la survie. Ce chapitre jette les bases du reste du livre en fournissant aux lecteurs une base solide pour comprendre les concepts suivants. Chapitre 1 : Introduction au Data Engineering Ce chapitre présente le concept de Data Engineering et son importance à l'ère numérique moderne.
Ingeniería de datos controlada e incontrolada para datos multimedia En el mundo actual, la tecnología evoluciona a una velocidad sin precedentes y es importante comprender su proceso de evolución para garantizar la supervivencia de la humanidad y la unidad entre las naciones. libro Supervised and Unsupervised Data Engineering for Multimedia Data ofrece una visión general completa del desarrollo de técnicas de ingeniería de datos para datos multimedia, resaltando sus posibles aplicaciones y problemas. Este libro es un recurso valioso para investigadores, profesionales y estudiantes que desean conocer las últimas tendencias en ingeniería de datos y sus aplicaciones prácticas. libro comienza discutiendo la importancia de entender la evolución de la tecnología y su impacto en la sociedad. Destaca la necesidad de generar un paradigma personal para percibir el proceso tecnológico del desarrollo del conocimiento moderno como base de supervivencia. Este capítulo sienta las bases para el resto del libro, proporcionando a los lectores una base sólida para comprender los siguientes conceptos. Capítulo 1: Introducción a la Ingeniería de Datos Este capítulo presenta el concepto de Ingeniería de Datos y su significado en la era digital moderna.
Ingegneria dei dati per i dati multimediali controllata e incontrollata Nel mondo moderno, la tecnologia evolve ad una velocità senza precedenti ed è importante comprendere il processo di evoluzione per garantire la sopravvivenza dell'umanità e la coesione tra le nazioni. Il libro «Supervised and Unsupervised Data Engineering for Multimedia Data» fornisce una panoramica completa dello sviluppo di tecniche di ingegneria multimediale per i dati multimediali, evidenziando potenziali applicazioni e problemi. Questo libro è una preziosa risorsa per ricercatori, professionisti e studenti che vogliono conoscere le ultime tendenze dell'ingegneria dei dati e le loro applicazioni pratiche. Il libro inizia con un dibattito sull'importanza di comprendere l'evoluzione della tecnologia e il loro impatto sulla società. Sottolinea la necessità di sviluppare un paradigma personale per la percezione del processo tecnologico di sviluppo della conoscenza moderna come base di sopravvivenza. Questo capitolo pone le basi per il resto del libro, fornendo ai lettori una base solida per comprendere i seguenti concetti. Capitolo 1: Introduzione a Data Engineering Questo capitolo presenta il concetto di Data Engineering e il suo significato nell'era digitale moderna.
Kontrolliertes und unkontrolliertes Data Engineering für Multimedia-Daten In der heutigen Welt entwickeln sich Technologien in einer beispiellosen Geschwindigkeit, und es ist wichtig, den Prozess ihrer Entwicklung zu verstehen, um das Überleben der Menschheit und die Einheit zwischen den Nationen zu gewährleisten. Das Buch „Supervised and Unsupervised Data Engineering for Multimedia Data“ gibt einen umfassenden Überblick über die Entwicklung von Data-Engineering-Methoden für Multimedia-Daten und beleuchtet deren Einsatzmöglichkeiten und Herausforderungen. Dieses Buch ist eine wertvolle Ressource für Forscher, Praktiker und Studenten, die sich über die neuesten Trends im Data Engineering und ihre praktischen Anwendungen informieren möchten. Das Buch beginnt mit einer Diskussion über die Bedeutung des Verständnisses der Technologieentwicklung und ihrer Auswirkungen auf die Gesellschaft. Es betont die Notwendigkeit, ein persönliches Paradigma für die Wahrnehmung des technologischen Prozesses der Entwicklung des modernen Wissens als Grundlage des Überlebens zu entwickeln. Dieses Kapitel legt den Grundstein für den Rest des Buches und bietet den sern eine solide Grundlage, um die folgenden Konzepte zu verstehen. Kapitel 1: Einführung in das Data Engineering In diesem Kapitel wird das Konzept des Data Engineering und seine Bedeutung im heutigen digitalen Zeitalter vorgestellt.
''
Multimedya Verileri için Kontrollü ve Kontrolsüz Veri Mühendisliği Günümüz dünyasında, teknoloji benzeri görülmemiş bir hızla gelişmektedir ve insanlığın hayatta kalmasını ve uluslar arasındaki birliği sağlamak için evrim süreçlerini anlamak önemlidir. Multimedya Verileri için Denetlenen ve Denetlenmeyen Veri Mühendisliği kitabı, multimedya verileri için veri mühendisliği tekniklerinin geliştirilmesine kapsamlı bir genel bakış sunarak, potansiyel uygulamalarını ve zorluklarını vurgulamaktadır. Bu kitap, veri mühendisliğindeki en son eğilimler ve pratik uygulamaları hakkında bilgi edinmek isteyen araştırmacılar, uygulayıcılar ve öğrenciler için değerli bir kaynaktır. Kitap, teknolojinin evrimini ve toplum üzerindeki etkisini anlamanın önemini tartışarak başlıyor. Hayatta kalmanın temeli olarak modern bilginin gelişiminin teknolojik sürecinin algılanması için kişisel bir paradigma geliştirme ihtiyacını vurgulamaktadır. Bu bölüm, kitabın geri kalanı için zemin hazırlar ve okuyuculara aşağıdaki kavramları anlamak için sağlam bir temel sağlar. Bölüm 1: Veri Mühendisliğine Giriş Bu bölüm Veri Mühendisliği kavramını ve günümüz dijital çağındaki etkilerini tanıtmaktadır.
多媒體數據的可控且不受控制的數據工程在當今世界中,技術以前所未有的速度發展,了解其演變過程,以確保人類生存和國家之間的團結非常重要。「多媒體數據受控和無監督的數據工程」一書全面概述了多媒體數據數據工程技術的發展,突出了其潛在應用和挑戰。這本書是研究人員、從業人員和學生希望了解數據工程的最新趨勢及其實際應用的寶貴資源。本書首先討論了了解技術演變及其對社會影響的重要性。它強調需要建立個人範式,將現代知識的技術發展作為生存的基礎。本章為本書的其余部分奠定了基礎,為讀者提供了了解以下概念的堅實基礎。第一章:數據工程簡介本章介紹了數據工程的概念及其在現代數字時代的意義。

You may also be interested in:

Strategic Software Engineering Software Engineering Beyond the Code
Python for Data Science A step-by-step Python Programming Guide to Master Big Data, Analysis, Machine Learning, and Artificial Intelligence
Machine Learning For Beginners A Math Free Introduction for Business and Individuals to Machine Learning, Big Data, Data Science, and Neural Networks
Python Data Science The Bible. The Ultimate Beginner’s Guide to Learn Data Analysis, from the Basics and Essentials, to Advance Content! (Python Programming, Python Crash Course, Coding Made Easy Book
Data Analysis Foundations with Python Master Python and Data Analysis using NumPy, Pandas, Matplotlib, and Seaborn A Hands-On Guide with Projects and Case Studies
Data Analysis Foundations with Python: Master Python and Data Analysis using NumPy, Pandas, Matplotlib, and Seaborn: A Hands-On Guide with Projects and Case Studies.
Data Analysis Foundations with Python Master Python and Data Analysis using NumPy, Pandas, Matplotlib, and Seaborn A Hands-On Guide with Projects and Case Studies
PYTHON 2 Books in 1 Python Programming & Data Science. Master Data Analysis in Less than 7 Days and Discover the Secrets of Machine Learning with Step-by-Step Exercises
Python for Data Analysis The Ultimate Beginner|s Guide to Learn programming in Python for Data Science with Pandas and NumPy, Master Statistical Analysis, and Visualization
Near Extensions and Alignment of Data in R^n: Whitney extensions of near isometries, shortest paths, equidistribution, clustering and non-rigid alignment of data in Euclidean space
Ultimate Python Libraries for Data Analysis and Visualization Leverage Pandas, NumPy, Matplotlib, Seaborn, Julius AI and No-Code Tools for Data Acquisition, Visualization, and Statistical Analysis
Python for Data Analysis A Basic Guide for Beginners to Learn the Language of Python Programming Codes Applied to Data Analysis with Libraries Software Pandas, Numpy, and IPython
Data Science 2 Books in 1 Python Programming & Python for Data Science, The Ultimate Guide to Learn Machine Learning and Predictive Analytics from Scratch with Hands-On Projects
Managing Cloud Native Data on Kubernetes Architecting Cloud Native Data Services Using Open Source Technology (Final)
Industry 4.0 Convergence with AI, IoT, Big Data and Cloud Computing: Fundamentals, Challenges and Applications (IoT and Big Data Analytics)
Algorithms and Data Structures with Python: An interactive learning experience: Comprehensive introduction to data structures and algorithms (Spanish Edition)
Data Science and Machine Learning Interview Questions Using R Crack the Data Scientist and Machine Learning Engineers Interviews with Ease
Data Science and Machine Learning Interview Questions Using R: Crack the Data Scientist and Machine Learning Engineers Interviews with Ease
Data Analysis In Microsoft Excel Guided Project - Healthcare Master Skills in Data Analysis and Excel A Healthcare Data Guided Project
Data Analysis In Microsoft Excel: Guided Project - Healthcare: Master Skills in Data Analysis and Excel: A Healthcare Data Guided Project
Data Analysis In Microsoft Excel Guided Project - Healthcare Master Skills in Data Analysis and Excel A Healthcare Data Guided Project
Data Analytics Principles, Tools, and Practices A Complete Guide for Advanced Data Analytics Using the Latest Trends, Tools
IoT Data Analytics using Python: Learn how to use Python to collect, analyze, and visualize IoT data (English Edition)
Reproducible Data Science with Pachyderm: Learn how to build version-controlled, end-to-end data pipelines using Pachyderm 2.0
Python For Data Analysis A Step-by-Step Guide to Pandas, NumPy, and SciPy for Data Wrangling, Analysis, and Visualization
Managing Cloud Native Data on Kubernetes: Architecting Cloud Native Data Services Using Open Source Technology
Introduction to Algorithms & Data Structures 3 Learn Linear Data Structures with Videos & Interview Questions
Python Programming 2 Books in 1 Python for Data Analysis and Science with Big Data Analysis, Statistics and Machine Learning
Practical Data Privacy: Enhancing Privacy and Security in Data
The Data Literacy Blueprint (Data Literacy Fundamentals Book 1)
Algorithms and Data Structures with Python An interactive learning experience Comprehensive introduction to data structures and algorithms
Python in Power BI Unleash the Power of Python for Dynamic Data Analysis A Comprehensive Guide to Data Visualization
Python in Power BI Unleash the Power of Python for Dynamic Data Analysis A Comprehensive Guide to Data Visualization
Textual Data Science with R (Chapman & Hall/CRC Computer Science & Data Analysis)
Python Data Science: Deep Learning Guide for Beginners with Data Science. Python Programming and Crush Course.
Data Modeling with Snowflake: A practical guide to accelerating Snowflake development using universal data modeling techniques
Algorithms and Data Structures with Python An interactive learning experience Comprehensive introduction to data structures and algorithms
Python for Data Analysis A Complete Crash Course on Python for Data Science to Learn Essential Tools and Python Libraries, NumPy, Pandas, Jupyter Notebook, Analysis and Visualization
Python Data Science An Ultimate Guide for Beginners to Learn Fundamentals of Data Science Using Python
Easy Learning Data Structures & Algorithms C# Graphically learn data structures and algorithms better than before