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5 books on AI for Big Data [PDF]
October 23, 2024 | 22 |
These books explain how AI can be used to extract meaningful insights, detect patterns from vast and complex data sources and support data-driven decisions.
1. Industrial Applications of Big Data, AI, and Blockchain
2024 by El Samad, Mahmoud, Nassreddine, Ghalia, El-Chaarani, Hani, El Nemar, Sam
"Industrial Applications of Big Data, AI and Blockchain" explores how blockchain, initially developed for cryptocurrency, has become a cornerstone technology across various sectors, including finance, healthcare and e-governance, often supported by Big Data and AI. Emphasizing blockchain's peer-to-peer approach that operates without a central authority, the book also addresses the necessity of constant monitoring and updates, especially for maintaining data privacy and security in sensitive areas like healthcare. It delves into AI's automation impact across business, finance, healthcare, marketing and governance, highlighting how AI algorithms and natural language processing enhance decision-making and drive industry transformation. This book is perfect for researchers, business leaders, tech enthusiasts and anyone interested in understanding the transformative potential of these technologies.
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2. 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
In a universe not so far away, where clouds aren’t just fluffy things in the sky but the bedrock of our digital existence, Convergence of Cloud with AI for Big Data Analytics: Foundations and Innovation takes readers on a whirlwind tour of the spectacularly complex love triangle between AI, Big Data and Cloud Computing. With all the charm of a well-oiled improbability drive, the book explores how these three juggernauts of tech—backed by wireless gizmos and occasionally befuddled engineers—have teamed up to tackle the galaxy’s most pressing problems, like latency, energy consumption and the eternal question of why your healthcare app keeps crashing. Spanning 17 knowledge-packed chapters, it unpacks not only their latest adventures but also the irritating hurdles still in the way, offering solutions that range from brilliant to downright inspired. A must-read for anyone hoping to decipher the cosmic code of modern computing—or just impress their friends at the next AI conference.
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3. Transforming Management with AI, Big-Data, and IoT
2022 by Fadi Al-Turjman, Satya Prakash Yadav, Manoj Kumar, Vibhash Yadav, Thompson Stephan
Transforming Management with AI, Big-Data and IoTis the kind of book that would whisper sweet nothings to your managerial instincts if only it weren't too busy revolutionizing everything from your coffee machine to the orbital trajectory of satellite education systems. Picture a universe where artificial intelligence and the Internet of Things are not just polite houseguests in the realms of law, politics and economics, but audacious party-crashers in autonomous transportation and space exploration. Brimming with examples, exercises and a smattering of high-brow empirical research (just to keep your brain on its toes), the authors untangle the Gordian knot of trust dynamics, from global markets to your neighbor’s dodgy Wi-Fi. Whether you’re after groundbreaking case studies or the kind of cutting-edge AI features that make spreadsheets weep with joy, this book serves it all up with an air of "Well, obviously the future was going to be like this. Didn’t you get the memo?"
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4. Enabling AI Applications in Data Science
2020 by Aboul-Ella Hassanien, Mohamed Hamed N. Taha, Nour Eldeen M. Khalifa
In the grand and sprawling universe of books that try to make sense of artificial intelligence, Enabling AI Applications in Data Science stands out as the sort of guide that might very well leave your neurons applauding. Imagine, if you will, a realm where machines get smarter not because they want to, but because an avalanche of data insists on it. This book cheerfully dissects the dance of AI and data science, where precision and efficiency waltz thanks to breakthroughs in storage, processing and an unapologetic glut of information. If you've ever wondered how AI gets so clever—spoiler: it involves lots of data and clever humans—this book is like having a backstage pass to the cosmic show of algorithms and insights, minus the intergalactic bureaucracy.
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5. Smarter Data Science: Succeeding with Enterprise-Grade Data and AI Projects
2020 by Neal Fishman, Cole Stryker
In the sprawling, often bewildering universe of enterprise-grade data science and AI, where projects tend to evaporate into chaos faster than a Vogon poetry reading clears a room, Smarter Data Science: Succeeding with Enterprise-Grade Data and AI Projects steps in like a well-timed towel. Written with a clarity that might even make a supercomputer sigh in relief, this book gently guides business professionals—whether they’re directors, managers, or just people stuck pretending to know what “prescriptive analytics” means—through the labyrinthine perils of fragmented initiatives, rogue data silos and ambitions doomed to flop noisily into the void. Instead of yet another catastrophic failure that leaves everyone blaming Marvin, you'll find here a lucid, planet-saving blueprint for transforming your data science woes into something that actually works: scalable, sustainable AI solutions that even the most skeptical IT leaders might grudgingly applaud. So, grab this guide, hitch a ride on the data highway and discover that the secret to life, the universe and everything might just be... smarter data science.
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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. Industrial Applications of Big Data, AI, and Blockchain
2024 by El Samad, Mahmoud, Nassreddine, Ghalia, El-Chaarani, Hani, El Nemar, Sam
"Industrial Applications of Big Data, AI and Blockchain" explores how blockchain, initially developed for cryptocurrency, has become a cornerstone technology across various sectors, including finance, healthcare and e-governance, often supported by Big Data and AI. Emphasizing blockchain's peer-to-peer approach that operates without a central authority, the book also addresses the necessity of constant monitoring and updates, especially for maintaining data privacy and security in sensitive areas like healthcare. It delves into AI's automation impact across business, finance, healthcare, marketing and governance, highlighting how AI algorithms and natural language processing enhance decision-making and drive industry transformation. This book is perfect for researchers, business leaders, tech enthusiasts and anyone interested in understanding the transformative potential of these technologies.
Download PDF
2. 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
In a universe not so far away, where clouds aren’t just fluffy things in the sky but the bedrock of our digital existence, Convergence of Cloud with AI for Big Data Analytics: Foundations and Innovation takes readers on a whirlwind tour of the spectacularly complex love triangle between AI, Big Data and Cloud Computing. With all the charm of a well-oiled improbability drive, the book explores how these three juggernauts of tech—backed by wireless gizmos and occasionally befuddled engineers—have teamed up to tackle the galaxy’s most pressing problems, like latency, energy consumption and the eternal question of why your healthcare app keeps crashing. Spanning 17 knowledge-packed chapters, it unpacks not only their latest adventures but also the irritating hurdles still in the way, offering solutions that range from brilliant to downright inspired. A must-read for anyone hoping to decipher the cosmic code of modern computing—or just impress their friends at the next AI conference.
Download PDF
3. Transforming Management with AI, Big-Data, and IoT
2022 by Fadi Al-Turjman, Satya Prakash Yadav, Manoj Kumar, Vibhash Yadav, Thompson Stephan
Transforming Management with AI, Big-Data and IoTis the kind of book that would whisper sweet nothings to your managerial instincts if only it weren't too busy revolutionizing everything from your coffee machine to the orbital trajectory of satellite education systems. Picture a universe where artificial intelligence and the Internet of Things are not just polite houseguests in the realms of law, politics and economics, but audacious party-crashers in autonomous transportation and space exploration. Brimming with examples, exercises and a smattering of high-brow empirical research (just to keep your brain on its toes), the authors untangle the Gordian knot of trust dynamics, from global markets to your neighbor’s dodgy Wi-Fi. Whether you’re after groundbreaking case studies or the kind of cutting-edge AI features that make spreadsheets weep with joy, this book serves it all up with an air of "Well, obviously the future was going to be like this. Didn’t you get the memo?"
Download PDF
4. Enabling AI Applications in Data Science
2020 by Aboul-Ella Hassanien, Mohamed Hamed N. Taha, Nour Eldeen M. Khalifa
In the grand and sprawling universe of books that try to make sense of artificial intelligence, Enabling AI Applications in Data Science stands out as the sort of guide that might very well leave your neurons applauding. Imagine, if you will, a realm where machines get smarter not because they want to, but because an avalanche of data insists on it. This book cheerfully dissects the dance of AI and data science, where precision and efficiency waltz thanks to breakthroughs in storage, processing and an unapologetic glut of information. If you've ever wondered how AI gets so clever—spoiler: it involves lots of data and clever humans—this book is like having a backstage pass to the cosmic show of algorithms and insights, minus the intergalactic bureaucracy.
Download PDF
5. Smarter Data Science: Succeeding with Enterprise-Grade Data and AI Projects
2020 by Neal Fishman, Cole Stryker
In the sprawling, often bewildering universe of enterprise-grade data science and AI, where projects tend to evaporate into chaos faster than a Vogon poetry reading clears a room, Smarter Data Science: Succeeding with Enterprise-Grade Data and AI Projects steps in like a well-timed towel. Written with a clarity that might even make a supercomputer sigh in relief, this book gently guides business professionals—whether they’re directors, managers, or just people stuck pretending to know what “prescriptive analytics” means—through the labyrinthine perils of fragmented initiatives, rogue data silos and ambitions doomed to flop noisily into the void. Instead of yet another catastrophic failure that leaves everyone blaming Marvin, you'll find here a lucid, planet-saving blueprint for transforming your data science woes into something that actually works: scalable, sustainable AI solutions that even the most skeptical IT leaders might grudgingly applaud. So, grab this guide, hitch a ride on the data highway and discover that the secret to life, the universe and everything might just be... smarter data science.
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
