Raul V. Rodriguez – författare

Machine Learning is an integral tool in a business analyst’s arsenal because the rate at which data is being generated from different sources is increasing and working on complex unstructured data is becoming inevitable. Data collection, data cleaning, and data mining are rapidly becoming more difficult to analyze than just importing information from a primary or secondary source. The machine learning model plays a crucial role in predicting the future performance and results of a company. In real-time, data collection and data wrangling are the important steps in deploying the models. Analytics is a tool for visualizing and steering data and statistics. Business analysts can work with different datasets -- choosing an appropriate machine learning model results in accurate analyzing, forecasting the future, and making informed decisions.

The global machine learning market was valued at $1.58 billion in 2017 and is expected to reach $20.83 billion in 2024 -- growing at a CAGR of 44.06% between 2017 and 2024. The authors have compiled important knowledge on machine learning real-time applications in business analytics. This book enables readers to get broad knowledge in the field of machine learning models and to carry out their future research work. The future trends of machine learning for business analytics are explained with real case studies.

Essentially, this book acts as a guide to all business analysts. The authors blend the basics of data analytics and machine learning and extend its application to business analytics. This book acts as a superb introduction and covers the applications and implications of machine learning. The authors provide first-hand experience of the applications of machine learning for business analytics in the section on real-time analysis. Case studies put the theory into practice so that you may receive hands-on experience with machine learning and data analytics. This book is a valuable source for practitioners, industrialists, technologists, and researchers.

Machine Learning is an integral tool in a business analyst’s arsenal because the rate at which data is being generated from different sources is increasing and working on complex unstructured data is becoming inevitable. Data collection, data cleaning, and data mining are rapidly becoming more difficult to analyze than just importing information from a primary or secondary source. The machine learning model plays a crucial role in predicting the future performance and results of a company. In real-time, data collection and data wrangling are the important steps in deploying the models. Analytics is a tool for visualizing and steering data and statistics. Business analysts can work with different datasets -- choosing an appropriate machine learning model results in accurate analyzing, forecasting the future, and making informed decisions.

The global machine learning market was valued at $1.58 billion in 2017 and is expected to reach $20.83 billion in 2024 -- growing at a CAGR of 44.06% between 2017 and 2024. The authors have compiled important knowledge on machine learning real-time applications in business analytics. This book enables readers to get broad knowledge in the field of machine learning models and to carry out their future research work. The future trends of machine learning for business analytics are explained with real case studies.

Essentially, this book acts as a guide to all business analysts. The authors blend the basics of data analytics and machine learning and extend its application to business analytics. This book acts as a superb introduction and covers the applications and implications of machine learning. The authors provide first-hand experience of the applications of machine learning for business analytics in the section on real-time analysis. Case studies put the theory into practice so that you may receive hands-on experience with machine learning and data analytics. This book is a valuable source for practitioners, industrialists, technologists, and researchers.

Artificial Intelligence and Knowledge Processing play a vital role in various automation industries and their functioning in converting traditional industries to AI-based factories. This book acts as a guide and blends the basics of Artificial Intelligence in various domains, which include Machine Learning, Deep Learning, Artificial Neural Networks, and Expert Systems, and extends their application in all sectors.

Artificial Intelligence and Knowledge Processing: Improved Decision-Making and Prediction, discusses the designing of new AI algorithms used to convert general applications to AI-based applications. It highlights different Machine Learning and Deep Learning models for various applications used in healthcare and wellness, agriculture, and automobiles. The book offers an overview of the rapidly growing and developing field of AI applications, along with Knowledge of Engineering, and Business Analytics. Real-time case studies are included across several different fields such as Image Processing, Text Mining, Healthcare, Finance, Digital Marketing, and HR Analytics. The book also introduces a statistical background and probabilistic framework to enhance the understanding of continuous distributions. Topics such as Ensemble Models, Deep Learning Models, Artificial Neural Networks, Expert Systems, and Decision-Based Systems round out the offerings of this book.

This multi-contributed book is a valuable source for researchers, academics, technologists, industrialists, practitioners, and all those who wish to explore the applications of AI, Knowledge Processing, Deep Learning, and Machine Learning.

Artificial Intelligence and Knowledge Processing play a vital role in various automation industries and their functioning in converting traditional industries to AI-based factories. This book acts as a guide and blends the basics of Artificial Intelligence in various domains, which include Machine Learning, Deep Learning, Artificial Neural Networks, and Expert Systems, and extends their application in all sectors.

Artificial Intelligence and Knowledge Processing: Improved Decision-Making and Prediction, discusses the designing of new AI algorithms used to convert general applications to AI-based applications. It highlights different Machine Learning and Deep Learning models for various applications used in healthcare and wellness, agriculture, and automobiles. The book offers an overview of the rapidly growing and developing field of AI applications, along with Knowledge of Engineering, and Business Analytics. Real-time case studies are included across several different fields such as Image Processing, Text Mining, Healthcare, Finance, Digital Marketing, and HR Analytics. The book also introduces a statistical background and probabilistic framework to enhance the understanding of continuous distributions. Topics such as Ensemble Models, Deep Learning Models, Artificial Neural Networks, Expert Systems, and Decision-Based Systems round out the offerings of this book.

This multi-contributed book is a valuable source for researchers, academics, technologists, industrialists, practitioners, and all those who wish to explore the applications of AI, Knowledge Processing, Deep Learning, and Machine Learning.

Artificial intelligence (AI) is transforming the business world at an unprecedented pace. From automating mundane tasks to predicting consumer behaviour, AI is changing the way businesses operate across all sectors. This book is an exploration of AI in business applications, highlighting the diverse range of ways in which AI is being used across different industries.

The book begins with an overview of AI in business and its impact on the workforce. It then explores the role of AI in marketing, advertising, and tourism. The use of AI in personalized recommendations and chatbots is discussed in detail. The book then moves on to examine how AI is changing the retail industry, improving supply chain management, and enhancing the customer experience.

The media and entertainment industry is also examined, with a focus on how AI is being used to personalize content and improve the user experience. The book also explores the use of AI in human resources, insurance, legal, and finance. The impact of AI on talent identification, recruitment, underwriting, document analysis, and financial forecasting is discussed in detail.

In the healthcare and sports industries, AI is transforming the way we approach diagnosis, treatment, and training. The book examines how AI is being used to analyse medical images, develop personalized treatment plans, and improve patient outcomes. The use of AI in sports performance analysis is also discussed in detail.

Finally, the book explores the use of AI in agriculture, energy, education, and the public sector. The potential of AI to optimize crop yields, reduce energy consumption, and improve the quality of education is discussed in detail. The book also examines how AI is being used to improve public services, such as transportation and emergency services.

This book is a valuable resource for academics, researchers, professionals, and policymakers who are interested in understanding the potential of AI in the business world. The contributions from leading experts and researchers provide a comprehensive overview of AI in business applications, and how it is transforming different sectors.

The book also examines the ethical dilemmas that arise from the use of AI in business, such as the impact on privacy and data security, and the potential for bias in AI algorithms. It provides valuable insights into how businesses can ensure that the use of AI is ethical and responsible.

In conclusion, this book is a must-read for anyone interested in the potential of AI in the business world. It provides a comprehensive overview of AI in business applications and how it is transforming different sectors. The book examines the ethical dilemmas that arise from the use of AI in business, providing valuable insights into how businesses can ensure that the use of AI is ethical and responsible. We hope that readers will find this book informative and thought-provoking.

Artificial intelligence (AI) is transforming the business world at an unprecedented pace. From automating mundane tasks to predicting consumer behaviour, AI is changing the way businesses operate across all sectors. This book is an exploration of AI in business applications, highlighting the diverse range of ways in which AI is being used across different industries.

The book begins with an overview of AI in business and its impact on the workforce. It then explores the role of AI in marketing, advertising, and tourism. The use of AI in personalized recommendations and chatbots is discussed in detail. The book then moves on to examine how AI is changing the retail industry, improving supply chain management, and enhancing the customer experience.

The media and entertainment industry is also examined, with a focus on how AI is being used to personalize content and improve the user experience. The book also explores the use of AI in human resources, insurance, legal, and finance. The impact of AI on talent identification, recruitment, underwriting, document analysis, and financial forecasting is discussed in detail.

In the healthcare and sports industries, AI is transforming the way we approach diagnosis, treatment, and training. The book examines how AI is being used to analyse medical images, develop personalized treatment plans, and improve patient outcomes. The use of AI in sports performance analysis is also discussed in detail.

Finally, the book explores the use of AI in agriculture, energy, education, and the public sector. The potential of AI to optimize crop yields, reduce energy consumption, and improve the quality of education is discussed in detail. The book also examines how AI is being used to improve public services, such as transportation and emergency services.

This book is a valuable resource for academics, researchers, professionals, and policymakers who are interested in understanding the potential of AI in the business world. The contributions from leading experts and researchers provide a comprehensive overview of AI in business applications, and how it is transforming different sectors.

The book also examines the ethical dilemmas that arise from the use of AI in business, such as the impact on privacy and data security, and the potential for bias in AI algorithms. It provides valuable insights into how businesses can ensure that the use of AI is ethical and responsible.

In conclusion, this book is a must-read for anyone interested in the potential of AI in the business world. It provides a comprehensive overview of AI in business applications and how it is transforming different sectors. The book examines the ethical dilemmas that arise from the use of AI in business, providing valuable insights into how businesses can ensure that the use of AI is ethical and responsible. We hope that readers will find this book informative and thought-provoking.

The metaverse is the future of business applications and models, and this ground-breaking book points and details a complete and clear picture of how the metaverse can impact the various business segments and how the human element will be maintained within the evolutionary change. This book serves as a guide for those planning to implement and expand the metaverse in their business as well as those already using it on limited levels. Simulated intelligence innovation can reveal intricate and significant examples in robust and information-rich situations that posture difficulties for human insight.

In addition, similar to other burgeoning advancements, the experience and aptitudes accumulated by vendors and consumers, alongside the steady analysis of interactions and information, empower metaverse calculations to be refined and improved. This book illustrates the current advancements and results and expands the analysis of human-centric metaverse applications to business segments and their future effects on overall enterprise management. Essentially, this book elaborates on the impact of the metaverse across business sectors through the use of case studies.

The metaverse is the future of business applications and models, and this ground-breaking book points and details a complete and clear picture of how the metaverse can impact the various business segments and how the human element will be maintained within the evolutionary change. This book serves as a guide for those planning to implement and expand the metaverse in their business as well as those already using it on limited levels. Simulated intelligence innovation can reveal intricate and significant examples in robust and information-rich situations that posture difficulties for human insight.

In addition, similar to other burgeoning advancements, the experience and aptitudes accumulated by vendors and consumers, alongside the steady analysis of interactions and information, empower metaverse calculations to be refined and improved. This book illustrates the current advancements and results and expands the analysis of human-centric metaverse applications to business segments and their future effects on overall enterprise management. Essentially, this book elaborates on the impact of the metaverse across business sectors through the use of case studies.

This book demonstrates how generative artificial intelligence (AI), a form of sophisticated AI technology, is transforming our knowledge of how the human mind functions in relation to business leadership and decision-making. It describes the most recent findings and applications of generative AI in psychology. The book explains the relationships between language, thinking, and behavior as well as how AI may aid in our understanding of learning, decision-making, and problem-solving. In addition, it discusses the significance of applying AI properly and ethically. This book provides a comprehensive overview of how AI is increasing our understanding of the mind and how it impacts each of us professionally.

This book demonstrates how generative artificial intelligence (AI), a form of sophisticated AI technology, is transforming our knowledge of how the human mind functions in relation to business leadership and decision-making. It describes the most recent findings and applications of generative AI in psychology. The book explains the relationships between language, thinking, and behavior as well as how AI may aid in our understanding of learning, decision-making, and problem-solving. In addition, it discusses the significance of applying AI properly and ethically. This book provides a comprehensive overview of how AI is increasing our understanding of the mind and how it impacts each of us professionally.

Artificial intelligence (AI) has been fast growing since its evolution and experiments with various new add-on features; human efficiency is one among those and the most controversial topic. This chapter focuses on its attention towards studying human consciousness and AI independently and in conjunction. It provides theories and arguments on AI being able to adapt human-like consciousness, cognitive abilities and ethics. This chapter studies responses of more than 300 candidates of the Indian population and compares it against the literature review. Furthermore, it also discusses whether AI could attain consciousness, develop its own set of cognitive abilities (cognitive AI), ethics (AI ethics) and overcome human beings’ efficiency. This chapter is a study of the Indian population’s understanding of consciousness, cognitive AI and AI ethics.

Artificial intelligence (AI) has been fast growing since its evolution and experiments with various new add-on features; human efficiency is one among those and the most controversial topic. This chapter focuses on its attention towards studying human consciousness and AI independently and in conjunction. It provides theories and arguments on AI being able to adapt human-like consciousness, cognitive abilities and ethics. This chapter studies responses of more than 300 candidates of the Indian population and compares it against the literature review. Furthermore, it also discusses whether AI could attain consciousness, develop its own set of cognitive abilities (cognitive AI), ethics (AI ethics) and overcome human beings’ efficiency. This chapter is a study of the Indian population’s understanding of consciousness, cognitive AI and AI ethics.

This comprehensive book provides an overview on the present status of positive organizational behaviour, offering insights on the growing body of research and scholarship, as well as suggestions for future directions in the field. Recent times have seen phenomenal and unprecedented changes in work settings, with many transitioning to hybrid or fully remote arrangements. In addition, unwarranted and unscrupulous application of technology, detrimental ramifications of work stress, and impaired well-being at work are posited to create an unsustainable work environment.

Bringing together leading experts from around the world, this collection synthesizes and captures the advancements within the discipline of positive organizational behaviour. It covers such topics as: psychological capital, work engagement interventions, self-efficacy, emotions and positive work behaviour, free will, resilience, work wellbeing, evolutionary psychology and positive workplace, cross-cultural positive organizational behaviour, common-good HRM practices, and methodological advances and challenges in positivity assessments.

The book offers a valuable resource for students and scholars of work/organizational psychology, organizational behaviour and applications of positive psychology. It is also a useful reference for organizations looking to understand and implement positive organizational policies in their workplaces.

This comprehensive book provides an overview on the present status of positive organizational behaviour, offering insights on the growing body of research and scholarship, as well as suggestions for future directions in the field. Recent times have seen phenomenal and unprecedented changes in work settings, with many transitioning to hybrid or fully remote arrangements. In addition, unwarranted and unscrupulous application of technology, detrimental ramifications of work stress, and impaired well-being at work are posited to create an unsustainable work environment.

Bringing together leading experts from around the world, this collection synthesizes and captures the advancements within the discipline of positive organizational behaviour. It covers such topics as: psychological capital, work engagement interventions, self-efficacy, emotions and positive work behaviour, free will, resilience, work wellbeing, evolutionary psychology and positive workplace, cross-cultural positive organizational behaviour, common-good HRM practices, and methodological advances and challenges in positivity assessments.

The book offers a valuable resource for students and scholars of work/organizational psychology, organizational behaviour and applications of positive psychology. It is also a useful reference for organizations looking to understand and implement positive organizational policies in their workplaces.