 |
6 books on AI Predictive Analytics [PDF]
Updated: February 02, 2024 | 21 |
Books on AI Predictive Analytics serve as essential guides for startups specializing in predictive analytics. These resources offer a comprehensive foundation in the field, covering topics such as machine learning, data preprocessing, feature selection, and model evaluation. They delve into the complexities of building accurate predictive models, emphasizing the significance of data-driven decision-making in various industries. Moreover, these books often include practical examples, case studies, and best practices, enabling startups to fine-tune their predictive analytics systems for optimal performance and real-world applications.
1. Artificial Intelligence for Business Analytics: Algorithms, Platforms and Application Scenarios
2023 by Felix Weber
"This book offers a succinct introduction to the essential aspects of leveraging artificial intelligence techniques for business analytics. It presents machine learning concepts and critical algorithms in an accessible manner within the context of business analytics technology. Furthermore, the book provides diverse application scenarios across various industries. Notably, it introduces the Business Analytics Model for Artificial Intelligence, serving as a reference procedure model for structuring business analytics and artificial intelligence projects within organizations. As businesses evolve, relying solely on traditional business intelligence and retrospective insights will no longer suffice. To remain competitive, companies must embrace business analytics, encompassing predictive analyses, automated decision-making, and the efficient use of vast datasets—an area where artificial intelligence methods play a pivotal role."
Download PDF
2. Evolving Predictive Analytics in Healthcare: New AI Techniques for Real-time Interventions
2022 by Abhishek Kumar, Ashutosh Kumar Dubey, Surbhi Bhatia, Swarn Avinash Kumar, Dac-Nhuong Le
"In this book, the application of practical predictive analytics in the healthcare domain, specifically for the diagnosis of current diseases, is explored, with a primary emphasis on medical imaging. Harnessing the advancements in AI, IoT, and data analytics, the book underscores the capacity to address real-time medical challenges, with an intensified focus on early prediction employing machine learning and deep learning algorithms. By integrating the capabilities of artificial intelligence with the Internet of 'Medical' Things, these algorithms can process patient data and characteristics, providing forecasts regarding future diagnoses, classifications, treatment strategies, and associated costs."
Download PDF
3. Predictive Analytics Applications with WEKA
2021 by Shuzlina Abdul Rahman & Sofianita Mutalib
"This book presents a straightforward yet engaging approach to applying data mining tools, with a particular focus on the Waikato Environment for Knowledge Analysis (WEKA), an open-source machine learning software. It offers a practical, hands-on exploration of the tools and techniques employed in data mining, meticulously breaking down the process into five sub-modules. Each sub-module begins with a comprehensive explanation of the topic to facilitate comprehension. The content covers various aspects, including data preparation, data cleansing, modeling, and results evaluation. Each sub-module concludes with a checklist activity and a discussion of common errors that learners might encounter. The book incorporates three illustrative case studies utilizing datasets from different sources, harnessing the capabilities of WEKA. This module serves as an excellent resource for individuals seeking a hands-on introduction to machine learning algorithms, with no extensive mathematical background required. 'Predictive Analytics Applications with WEKA' offers an accessible entry point into this rapidly evolving field, making it suitable for students and researchers interested in practical predictive analytics exercises."
Download PDF
4. Applying Predictive Analytics: Finding Value in Data
2019 by Richard V. McCarthy, Mary M. McCarthy, Wendy Ceccucci, Leila Halawi
"This textbook offers a pragmatic approach to the study of predictive analytics tailored for classroom settings. It centers on the application of analytics as a solution to real-world business challenges, offering comparisons of various modeling techniques, all elucidated through the use of SAS Enterprise Miner software examples. The authors demystify intricate algorithms, demonstrating how they can be effectively employed and explained in the context of enhancing business prospects. Each chapter introduces an initial vignette, illustrating real-life instances of how business analytics have been successfully employed across different facets of organizations to address issues or enhance outcomes. A continuous case study serves as an exemplar of how to construct and analyze a complex analytics model, harnessing its predictive capabilities for future outcomes."
Download PDF
5. Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die
2016 by Eric Siegel
"In this insightful and engrossing book, Eric Siegel, former Columbia University professor and founder of Predictive Analytics World, unveils the remarkable potential and potential pitfalls of predictive analytics. Siegel delves into a range of fascinating examples, revealing how predictive analytics can anticipate mortgage risks, forecast individuals' life events, and even predict the outcomes of seemingly unrelated phenomena. He elucidates why early retirement can correlate with shorter life spans and how organizations employ predictive analytics to anticipate various outcomes, from customer persuasion to health insurance predictions. The book sheds light on how machine learning and supercomputers are harnessed for counterterrorism efforts and how predictive modeling powered IBM's Watson in defeating human champions on Jeopardy! It also explores how companies unearth concealed truths, such as Target's ability to predict pregnancies and Hewlett-Packard's insight into employee attrition. As an ever-present science, predictive analytics profoundly shapes our daily experiences, making it imperative for both consumers and those affected by its insights to comprehend its formidable influence."
Download PDF
6. Predictive Analytics for Human Resources
2014 by Jac Fitz-enz, John Mattox, II
"Predictive Analytics for Human Resources serves as a practical and targeted how-to manual, offering invaluable guidance for those interested in engaging in predictive analytics. The book commences with an exploration of the fundamental concept of predictive analytics and proceeds to elucidate statistical examples through case simulations. Furthermore, it delves into topics such as internal coaching, mentoring, sponsoring, and offers insights into recruiting sponsors. This comprehensive resource encompasses a step-by-step guide for developing and implementing human resource analytics projects, replete with illustrative examples that demonstrate how to enter the market, construct a leadership model, and establish links to financial objectives through causal modeling. The book also delineates the ten essential steps for establishing an analytics function and outlines how to enhance organizational value by scrutinizing systems like staffing, training, and retention. Whether you are embarking on an HR analytics project or program, this comprehensive guide equips you with the knowledge and direction to initiate the process effectively."
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. Artificial Intelligence for Business Analytics: Algorithms, Platforms and Application Scenarios
2023 by Felix Weber
"This book offers a succinct introduction to the essential aspects of leveraging artificial intelligence techniques for business analytics. It presents machine learning concepts and critical algorithms in an accessible manner within the context of business analytics technology. Furthermore, the book provides diverse application scenarios across various industries. Notably, it introduces the Business Analytics Model for Artificial Intelligence, serving as a reference procedure model for structuring business analytics and artificial intelligence projects within organizations. As businesses evolve, relying solely on traditional business intelligence and retrospective insights will no longer suffice. To remain competitive, companies must embrace business analytics, encompassing predictive analyses, automated decision-making, and the efficient use of vast datasets—an area where artificial intelligence methods play a pivotal role."
Download PDF
2. Evolving Predictive Analytics in Healthcare: New AI Techniques for Real-time Interventions
2022 by Abhishek Kumar, Ashutosh Kumar Dubey, Surbhi Bhatia, Swarn Avinash Kumar, Dac-Nhuong Le
"In this book, the application of practical predictive analytics in the healthcare domain, specifically for the diagnosis of current diseases, is explored, with a primary emphasis on medical imaging. Harnessing the advancements in AI, IoT, and data analytics, the book underscores the capacity to address real-time medical challenges, with an intensified focus on early prediction employing machine learning and deep learning algorithms. By integrating the capabilities of artificial intelligence with the Internet of 'Medical' Things, these algorithms can process patient data and characteristics, providing forecasts regarding future diagnoses, classifications, treatment strategies, and associated costs."
Download PDF
3. Predictive Analytics Applications with WEKA
2021 by Shuzlina Abdul Rahman & Sofianita Mutalib
"This book presents a straightforward yet engaging approach to applying data mining tools, with a particular focus on the Waikato Environment for Knowledge Analysis (WEKA), an open-source machine learning software. It offers a practical, hands-on exploration of the tools and techniques employed in data mining, meticulously breaking down the process into five sub-modules. Each sub-module begins with a comprehensive explanation of the topic to facilitate comprehension. The content covers various aspects, including data preparation, data cleansing, modeling, and results evaluation. Each sub-module concludes with a checklist activity and a discussion of common errors that learners might encounter. The book incorporates three illustrative case studies utilizing datasets from different sources, harnessing the capabilities of WEKA. This module serves as an excellent resource for individuals seeking a hands-on introduction to machine learning algorithms, with no extensive mathematical background required. 'Predictive Analytics Applications with WEKA' offers an accessible entry point into this rapidly evolving field, making it suitable for students and researchers interested in practical predictive analytics exercises."
Download PDF
4. Applying Predictive Analytics: Finding Value in Data
2019 by Richard V. McCarthy, Mary M. McCarthy, Wendy Ceccucci, Leila Halawi
"This textbook offers a pragmatic approach to the study of predictive analytics tailored for classroom settings. It centers on the application of analytics as a solution to real-world business challenges, offering comparisons of various modeling techniques, all elucidated through the use of SAS Enterprise Miner software examples. The authors demystify intricate algorithms, demonstrating how they can be effectively employed and explained in the context of enhancing business prospects. Each chapter introduces an initial vignette, illustrating real-life instances of how business analytics have been successfully employed across different facets of organizations to address issues or enhance outcomes. A continuous case study serves as an exemplar of how to construct and analyze a complex analytics model, harnessing its predictive capabilities for future outcomes."
Download PDF
5. Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die
2016 by Eric Siegel
"In this insightful and engrossing book, Eric Siegel, former Columbia University professor and founder of Predictive Analytics World, unveils the remarkable potential and potential pitfalls of predictive analytics. Siegel delves into a range of fascinating examples, revealing how predictive analytics can anticipate mortgage risks, forecast individuals' life events, and even predict the outcomes of seemingly unrelated phenomena. He elucidates why early retirement can correlate with shorter life spans and how organizations employ predictive analytics to anticipate various outcomes, from customer persuasion to health insurance predictions. The book sheds light on how machine learning and supercomputers are harnessed for counterterrorism efforts and how predictive modeling powered IBM's Watson in defeating human champions on Jeopardy! It also explores how companies unearth concealed truths, such as Target's ability to predict pregnancies and Hewlett-Packard's insight into employee attrition. As an ever-present science, predictive analytics profoundly shapes our daily experiences, making it imperative for both consumers and those affected by its insights to comprehend its formidable influence."
Download PDF
6. Predictive Analytics for Human Resources
2014 by Jac Fitz-enz, John Mattox, II
"Predictive Analytics for Human Resources serves as a practical and targeted how-to manual, offering invaluable guidance for those interested in engaging in predictive analytics. The book commences with an exploration of the fundamental concept of predictive analytics and proceeds to elucidate statistical examples through case simulations. Furthermore, it delves into topics such as internal coaching, mentoring, sponsoring, and offers insights into recruiting sponsors. This comprehensive resource encompasses a step-by-step guide for developing and implementing human resource analytics projects, replete with illustrative examples that demonstrate how to enter the market, construct a leadership model, and establish links to financial objectives through causal modeling. The book also delineates the ten essential steps for establishing an analytics function and outlines how to enhance organizational value by scrutinizing systems like staffing, training, and retention. Whether you are embarking on an HR analytics project or program, this comprehensive guide equips you with the knowledge and direction to initiate the process effectively."
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
