Applying Predictive Analytics Within the Service Sector


Book Description

Value creation is a prime concern for any contemporary business. This can be accomplished through the incorporation of various techniques and processes, such as the integration of analytics to improve business functions. Applying Predictive Analytics Within the Service Sector is a pivotal reference source for the latest innovative perspectives on the incorporation of analysis techniques to enhance business performance. Examining a wide range of relevant topics, such as alternative clustering, recommender systems, and social media tools, this book is ideally designed for researchers, academics, students, professionals, and practitioners seeking scholarly material on business improvement in the service industry.




Data Mining and Machine Learning Applications


Book Description

DATA MINING AND MACHINE LEARNING APPLICATIONS The book elaborates in detail on the current needs of data mining and machine learning and promotes mutual understanding among research in different disciplines, thus facilitating research development and collaboration. Data, the latest currency of today’s world, is the new gold. In this new form of gold, the most beautiful jewels are data analytics and machine learning. Data mining and machine learning are considered interdisciplinary fields. Data mining is a subset of data analytics and machine learning involves the use of algorithms that automatically improve through experience based on data. Massive datasets can be classified and clustered to obtain accurate results. The most common technologies used include classification and clustering methods. Accuracy and error rates are calculated for regression and classification and clustering to find actual results through algorithms like support vector machines and neural networks with forward and backward propagation. Applications include fraud detection, image processing, medical diagnosis, weather prediction, e-commerce and so forth. The book features: A review of the state-of-the-art in data mining and machine learning, A review and description of the learning methods in human-computer interaction, Implementation strategies and future research directions used to meet the design and application requirements of several modern and real-time applications for a long time, The scope and implementation of a majority of data mining and machine learning strategies. A discussion of real-time problems. Audience Industry and academic researchers, scientists, and engineers in information technology, data science and machine and deep learning, as well as artificial intelligence more broadly.




Data Analytics Essentials You Always Wanted To Know


Book Description

Upon reading this book, you will get:  A fundamental comprehension of data analytics, including its types  An understanding of data analytics processes, software tools, and a range of analytics methodologies  A comprehension of what daily tasks and procedures the data analysts follow  An investigation into the vast field of big data analytics, covering its possibilities and challenges  An understanding of the existing legal frameworks, as well as ethical and privacy issues in data analytics  Application-based learning using a variety of real-world case studies From raw data to actionable insights - journey through the essentials of data analytics. Data Analytics Essentials You Always Wanted To Know is an approachable and captivating guide to understand the complicated world of data Data analytics is becoming increasingly important in today's data-driven society, and so has the demand for data analysts. Data Analytics Essentials You Always Wanted to Know (Data Analytics Essentials) is a comprehensive yet succinct manual, perfect for you if you are trying to understand the fundamentals of data analytics. It gives a concise introduction to data analytics and its current applicability. This book is a great tool for professionals switching to a career in data analytics and for students who want to learn the basics of data analytics. It will give you a strong foundation by explaining everything in an easy-to-understand language. Data Analytics Essentials goes beyond a theoretical manual and contains real-world case studies and fun facts to help you enhance your knowledge. The chapter summaries and self- assessment tests along with every chapter will help you test yourself as you move from one concept to the next.




Deep Learning for Healthcare Services IoT and Big Data Analytics


Book Description

This book highlights the applications of deep learning algorithms in implementing big data and IoT enabled smart solutions to treat and care for terminally ill patients. It presents 5 concise chapters showing how these technologies can empower the conventional doctor patient relationship in a more dynamic, transparent, and personalized manner. The key topics covered in this book include: - The Role of Deep Learning in Healthcare Industry: Limitations - Generative Adversarial Networks for Deep Learning in Healthcare - The Role of Blockchain in the Healthcare Sector - Brain Tumor Detection Based on Different Deep Neural Networks Key features include a thorough, research-based overview of technologies that can assist deep learning models in the healthcare sector, including architecture and industrial scope. The book also presents a robust image processing model for brain tumor screening. Through this book, the editors have attempted to combine numerous compelling views, guidelines and frameworks. Healthcare industry professionals will understand how Deep Learning can improve health care service delivery.




Predictive Analytics


Book Description

"Mesmerizing & fascinating..." —The Seattle Post-Intelligencer "The Freakonomics of big data." —Stein Kretsinger, founding executive of Advertising.com Award-winning | Used by over 30 universities | Translated into 9 languages An introduction for everyone. In this rich, fascinating — surprisingly accessible — introduction, leading expert Eric Siegel reveals how predictive analytics (aka machine learning) works, and how it affects everyone every day. Rather than a “how to” for hands-on techies, the book serves lay readers and experts alike by covering new case studies and the latest state-of-the-art techniques. Prediction is booming. It reinvents industries and runs the world. Companies, governments, law enforcement, hospitals, and universities are seizing upon the power. These institutions predict whether you're going to click, buy, lie, or die. Why? For good reason: predicting human behavior combats risk, boosts sales, fortifies healthcare, streamlines manufacturing, conquers spam, optimizes social networks, toughens crime fighting, and wins elections. How? Prediction is powered by the world's most potent, flourishing unnatural resource: data. Accumulated in large part as the by-product of routine tasks, data is the unsalted, flavorless residue deposited en masse as organizations churn away. Surprise! This heap of refuse is a gold mine. Big data embodies an extraordinary wealth of experience from which to learn. Predictive analytics (aka machine learning) unleashes the power of data. With this technology, the computer literally learns from data how to predict the future behavior of individuals. Perfect prediction is not possible, but putting odds on the future drives millions of decisions more effectively, determining whom to call, mail, investigate, incarcerate, set up on a date, or medicate. In this lucid, captivating introduction — now in its Revised and Updated edition — former Columbia University professor and Predictive Analytics World founder Eric Siegel reveals the power and perils of prediction: What type of mortgage risk Chase Bank predicted before the recession. Predicting which people will drop out of school, cancel a subscription, or get divorced before they even know it themselves. Why early retirement predicts a shorter life expectancy and vegetarians miss fewer flights. Five reasons why organizations predict death — including one health insurance company. How U.S. Bank and Obama for America calculated the way to most strongly persuade each individual. Why the NSA wants all your data: machine learning supercomputers to fight terrorism. How IBM's Watson computer used predictive modeling to answer questions and beat the human champs on TV's Jeopardy! How companies ascertain untold, private truths — how Target figures out you're pregnant and Hewlett-Packard deduces you're about to quit your job. How judges and parole boards rely on crime-predicting computers to decide how long convicts remain in prison. 182 examples from Airbnb, the BBC, Citibank, ConEd, Facebook, Ford, Google, the IRS, LinkedIn, Match.com, MTV, Netflix, PayPal, Pfizer, Spotify, Uber, UPS, Wikipedia, and more. How does predictive analytics work? This jam-packed book satisfies by demystifying the intriguing science under the hood. For future hands-on practitioners pursuing a career in the field, it sets a strong foundation, delivers the prerequisite knowledge, and whets your appetite for more. A truly omnipresent science, predictive analytics constantly affects our daily lives. Whether you are a




Big Data Analytics for Sustainable Computing


Book Description

Big data consists of data sets that are too large and complex for traditional data processing and data management applications. Therefore, to obtain the valuable information within the data, one must use a variety of innovative analytical methods, such as web analytics, machine learning, and network analytics. As the study of big data becomes more popular, there is an urgent demand for studies on high-level computational intelligence and computing services for analyzing this significant area of information science. Big Data Analytics for Sustainable Computing is a collection of innovative research that focuses on new computing and system development issues in emerging sustainable applications. Featuring coverage on a wide range of topics such as data filtering, knowledge engineering, and cognitive analytics, this publication is ideally designed for data scientists, IT specialists, computer science practitioners, computer engineers, academicians, professionals, and students seeking current research on emerging analytical techniques and data processing software.




Web Services: Concepts, Methodologies, Tools, and Applications


Book Description

Web service technologies are redefining the way that large and small companies are doing business and exchanging information. Due to the critical need for furthering automation, engagement, and efficiency, systems and workflows are becoming increasingly more web-based. Web Services: Concepts, Methodologies, Tools, and Applications is an innovative reference source that examines relevant theoretical frameworks, current practice guidelines, industry standards and standardization, and the latest empirical research findings in web services. Highlighting a range of topics such as cloud computing, quality of service, and semantic web, this multi-volume book is designed for computer engineers, IT specialists, software designers, professionals, researchers, and upper-level students interested in web services architecture, frameworks, and security.




Handbook of Big Data Research Methods


Book Description

This state-of-the-art Handbook provides an overview of the role of big data analytics in various areas of business and commerce, including accounting, finance, marketing, human resources, operations management, fashion retailing, information systems, and social media. It provides innovative ways of overcoming the challenges of big data research and proposes new directions for further research using descriptive, diagnostic, predictive, and prescriptive analytics.




Applied Big Data Analytics in Operations Management


Book Description

Operations management is a tool by which companies can effectively meet customers’ needs using the least amount of resources necessary. With the emergence of sensors and smart metering, big data is becoming an intrinsic part of modern operations management. Applied Big Data Analytics in Operations Management enumerates the challenges and creative solutions and tools to apply when using big data in operations management. Outlining revolutionary concepts and applications that help businesses predict customer behavior along with applications of artificial neural networks, predictive analytics, and opinion mining on business management, this comprehensive publication is ideal for IT professionals, software engineers, business professionals, managers, and students of management.




Research Anthology on Strategies for Using Social Media as a Service and Tool in Business


Book Description

Social media has become an integral part of society as social networking has become a main form of communication and human interaction. To stay relevant, businesses have adopted social media tactics to interact with consumers, conduct business, and remain competitive. Social technologies have reached a vital point in the business world, being essential in strategic decision-making processes, building relationships with consumers, marketing and branding efforts, and other important areas. While social media continues to gain importance in modern society, it is essential to determine how it functions in contemporary business. The Research Anthology on Strategies for Using Social Media as a Service and Tool in Business provides updated information on how businesses are strategically using social media and explores the role of social media in keeping businesses competitive in the global economy. The chapters will discuss how social tools work, what services businesses are utilizing, both the benefits and challenges to how social media is changing the modern business atmosphere, and more. This book is essential for researchers, instructors, social media managers, business managers, students, executives, practitioners, industry professionals, social media analysts, and all audiences interested in how social media is being used in modern businesses as both a service and integral tool.