 |
4 books on AI for Big Data [PDF]
Updated: March 05, 2024 | 22 |
Books on AI for Big Data offer startups invaluable insights into the powerful synergy between artificial intelligence and the processing of large-scale datasets. These resources provide a foundational understanding of how AI can be harnessed to extract meaningful insights, detect patterns, and make data-driven decisions from vast and complex data sources. They delve into topics such as machine learning algorithms, data preprocessing, and advanced analytics, providing startups with the necessary knowledge to handle the challenges and opportunities that big data presents. Moreover, these books often include practical examples, case studies, and best practices that can help startups optimize their big data processing workflows, ultimately allowing them to develop innovative AI solutions that can unlock the full potential of the enormous volumes of data generated in today's digital age, fostering a competitive advantage in data-driven decision-making and analytics.
1. Convergence of Cloud with AI for Big Data Analytics: Foundations and Innovation
2023 by Danda B. Rawat, Lalit K. Awasthi, Valentina Emilia Balas, Mohit Kumar, Jitendra Kumar Samriya
"This book extensively explores the foundational principles and practical applications of cloud computing, artificial intelligence (AI), and Big Data analytics while examining their convergence to enhance development and service delivery. Across its 17 chapters, the book adeptly navigates the interconnected realms of AI, cloud computing, and Big Data—three cutting-edge paradigms that have recently come to the forefront. These technologies have seen exponential growth in their applications, with the integration of AI, Cloud, and IoT (Internet of Things) relying on inputs from wireless devices. Despite the multitude of applications and progress made, several challenges, including security, latency, energy consumption, service allocation, healthcare services, and network lifetime, persist and must be addressed. 'Convergence of Cloud with AI for Big Data Analytics: Foundations and Innovation' provides a comprehensive exploration of these technologies, their interrelationships, state-of-the-art applications, challenges, proposed solutions, and strategies for framework enhancement. This book will be a valuable resource for researchers, post-graduate students in computing, software engineers, electrical engineers, data analysts, and cybersecurity professionals."
Download PDF
2. Transforming Management with AI, Big-Data, and IoT
2022 by Fadi Al-Turjman, Satya Prakash Yadav, Manoj Kumar, Vibhash Yadav, Thompson Stephan
"This book delves into the transformative impact of artificial intelligence (AI) and the Internet of Things (IoT) on various industries and domains. The authors initially highlight the broad reach of these technologies, spanning fields like law, politics, policy, economics, and their imminent influence on areas such as autonomous transportation, education, and space exploration. The book explores applications across diverse industries, offering comprehensive and well-illustrated discussions, complete with numerous examples and exercises. It delivers essential theoretical frameworks and presents the latest empirical research findings across various practical applications. Targeted at professionals seeking to enhance their comprehension of the strategic importance of trust within the information and knowledge society, this book covers trust dynamics at multiple levels, from the global economy down to individuals' roles in networked environments. The text encompasses research across numerous industries, highlighting how AI and IoT are reshaping the business and management landscape, and introduces novel AI and IoT features that enhance economic efficiency on both micro and macro scales. The book further examines case studies, providing tried-and-tested approaches for resolving common challenges in each application."
Download PDF
3. Enabling AI Applications in Data Science
2020 by Aboul-Ella Hassanien, Mohamed Hamed N. Taha, Nour Eldeen M. Khalifa
"This book offers an in-depth exploration of the most recent advancements and practical implementations within the realms of artificial intelligence and data science. Artificial intelligence has made significant strides in terms of precision and efficiency, largely owing to advancements in data storage and processing. Furthermore, the quality and quantity of data have played a pivotal role in augmenting the capabilities of artificial intelligence applications. With a focus on delivering the latest research breakthroughs in the field, this book delves into the synergistic relationship between artificial intelligence and data science."
Download PDF
4. Smarter Data Science: Succeeding with Enterprise-Grade Data and AI Projects
2020 by Neal Fishman, Cole Stryker
"Smarter Data Science: Succeeding with Enterprise-Grade Data and AI Projects" unveils the path to making data science an efficient, reliable tool that empowers business professionals to extract maximum value from their data. Enterprise-level data and AI initiatives often suffer from fragmentation, inadequate planning, isolation, and an inability to adapt to evolving business needs, leading to their high failure rates. This book offers a precise roadmap to sidestep these costly pitfalls. Data science is no longer the exclusive domain of data scientists; it has become a practical resource for business professionals, including managers, directors, IT leaders, and analysts. To maintain a competitive edge, organizations must broaden their utilization of data science capabilities, and "Smarter Data Science" equips them to achieve their ambitions in enterprise-level data projects and AI endeavors. It serves as a comprehensive guide for establishing a robust information architecture program that facilitates sustainable and scalable AI implementations. By mastering data management, organizations can transform their data science initiatives into fully scalable functions that are both prescriptive and reproducible. Armed with an understanding of data science fundamentals, practitioners are empowered to lead their organizations in the successful development and deployment of viable AI solutions.
Download PDF
How to download PDF:
1. Install Google Books Downloader
2. Enter Book ID to the search box and press Enter
3. Click "Download Book" icon and select PDF*
* - note that for yellow books only preview pages are downloaded
1. Convergence of Cloud with AI for Big Data Analytics: Foundations and Innovation
2023 by Danda B. Rawat, Lalit K. Awasthi, Valentina Emilia Balas, Mohit Kumar, Jitendra Kumar Samriya
"This book extensively explores the foundational principles and practical applications of cloud computing, artificial intelligence (AI), and Big Data analytics while examining their convergence to enhance development and service delivery. Across its 17 chapters, the book adeptly navigates the interconnected realms of AI, cloud computing, and Big Data—three cutting-edge paradigms that have recently come to the forefront. These technologies have seen exponential growth in their applications, with the integration of AI, Cloud, and IoT (Internet of Things) relying on inputs from wireless devices. Despite the multitude of applications and progress made, several challenges, including security, latency, energy consumption, service allocation, healthcare services, and network lifetime, persist and must be addressed. 'Convergence of Cloud with AI for Big Data Analytics: Foundations and Innovation' provides a comprehensive exploration of these technologies, their interrelationships, state-of-the-art applications, challenges, proposed solutions, and strategies for framework enhancement. This book will be a valuable resource for researchers, post-graduate students in computing, software engineers, electrical engineers, data analysts, and cybersecurity professionals."
Download PDF
2. Transforming Management with AI, Big-Data, and IoT
2022 by Fadi Al-Turjman, Satya Prakash Yadav, Manoj Kumar, Vibhash Yadav, Thompson Stephan
"This book delves into the transformative impact of artificial intelligence (AI) and the Internet of Things (IoT) on various industries and domains. The authors initially highlight the broad reach of these technologies, spanning fields like law, politics, policy, economics, and their imminent influence on areas such as autonomous transportation, education, and space exploration. The book explores applications across diverse industries, offering comprehensive and well-illustrated discussions, complete with numerous examples and exercises. It delivers essential theoretical frameworks and presents the latest empirical research findings across various practical applications. Targeted at professionals seeking to enhance their comprehension of the strategic importance of trust within the information and knowledge society, this book covers trust dynamics at multiple levels, from the global economy down to individuals' roles in networked environments. The text encompasses research across numerous industries, highlighting how AI and IoT are reshaping the business and management landscape, and introduces novel AI and IoT features that enhance economic efficiency on both micro and macro scales. The book further examines case studies, providing tried-and-tested approaches for resolving common challenges in each application."
Download PDF
3. Enabling AI Applications in Data Science
2020 by Aboul-Ella Hassanien, Mohamed Hamed N. Taha, Nour Eldeen M. Khalifa
"This book offers an in-depth exploration of the most recent advancements and practical implementations within the realms of artificial intelligence and data science. Artificial intelligence has made significant strides in terms of precision and efficiency, largely owing to advancements in data storage and processing. Furthermore, the quality and quantity of data have played a pivotal role in augmenting the capabilities of artificial intelligence applications. With a focus on delivering the latest research breakthroughs in the field, this book delves into the synergistic relationship between artificial intelligence and data science."
Download PDF
4. Smarter Data Science: Succeeding with Enterprise-Grade Data and AI Projects
2020 by Neal Fishman, Cole Stryker
"Smarter Data Science: Succeeding with Enterprise-Grade Data and AI Projects" unveils the path to making data science an efficient, reliable tool that empowers business professionals to extract maximum value from their data. Enterprise-level data and AI initiatives often suffer from fragmentation, inadequate planning, isolation, and an inability to adapt to evolving business needs, leading to their high failure rates. This book offers a precise roadmap to sidestep these costly pitfalls. Data science is no longer the exclusive domain of data scientists; it has become a practical resource for business professionals, including managers, directors, IT leaders, and analysts. To maintain a competitive edge, organizations must broaden their utilization of data science capabilities, and "Smarter Data Science" equips them to achieve their ambitions in enterprise-level data projects and AI endeavors. It serves as a comprehensive guide for establishing a robust information architecture program that facilitates sustainable and scalable AI implementations. By mastering data management, organizations can transform their data science initiatives into fully scalable functions that are both prescriptive and reproducible. Armed with an understanding of data science fundamentals, practitioners are empowered to lead their organizations in the successful development and deployment of viable AI solutions.
Download PDF
How to download PDF:
1. Install Google Books Downloader
2. Enter Book ID to the search box and press Enter
3. Click "Download Book" icon and select PDF*
* - note that for yellow books only preview pages are downloaded
