| Author | : Gitanjali Rahul Shinde,Asmita Balasaheb Kalamkar,Parikshit N. Mahalle,Nilanjan Dey |
| Publisher | : CRC Press |
| Release Date | : 2020-08-30 |
| ISBN 10 | : 1000204413 |
| Pages | : 68 pages |
Epidemic trend analysis, timeline progression, prediction, and recommendation are critical for initiating effective public health control strategies, and AI and data analytics play an important role in epidemiology, diagnostic, and clinical fronts. The focus of this book is data analytics for COVID-19, which includes an overview of COVID-19 in terms of epidemic/pandemic, data processing and knowledge extraction. Data sources, storage and platforms are discussed along with discussions on data models, their performance, different big data techniques, tools and technologies. This book also addresses the challenges in applying analytics to pandemic scenarios, case studies and control strategies. Aimed at Data Analysts, Epidemiologists and associated researchers, this book: discusses challenges of AI model for big data analytics in pandemic scenarios; explains how different big data analytics techniques can be implemented; provides a set of recommendations to minimize infection rate of COVID-19; summarizes various techniques of data processing and knowledge extraction; enables users to understand big data analytics techniques required for prediction purposes.
| Author | : Vijay Gadepally |
| Publisher | : Springer Nature |
| Release Date | : |
| ISBN 10 | : 3030710556 |
| Pages | : 329 pages |
| Author | : Wolfgang Wörndl |
| Publisher | : Springer Nature |
| Release Date | : |
| ISBN 10 | : 303065785X |
| Pages | : 329 pages |
| Author | : Aboul Ella Hassanien |
| Publisher | : Springer Nature |
| Release Date | : |
| ISBN 10 | : 3030633071 |
| Pages | : 329 pages |
| Author | : Chhabi Rani Panigrahi,Bibudhendu Pati,Mamata Rath,Rajkumar Buyya |
| Publisher | : CRC Press |
| Release Date | : 2021-05-10 |
| ISBN 10 | : 1000384977 |
| Pages | : 270 pages |
This book covers recent research on the COVID-19 pandemic. It includes the analysis, implementation, usage, and proposed ideas and models with architecture to handle the COVID-19 outbreak. Using advanced technologies such as artificial intelligence (AI) and machine learning (ML), techniques for data analysis, this book will be helpful to mitigate exposure and ensure public health. We know prevention is better than cure, so by using several ML techniques, researchers can try to predict the disease in its early stage and develop more effective medications and treatments. Computational technologies in areas like AI, ML, Internet of Things (IoT), and drone technologies underlie a range of applications that can be developed and utilized for this purpose. Because in most cases there is no one solution to stop the spreading of pandemic diseases, and the integration of several tools and tactics are needed. Many successful applications of AI, ML, IoT, and drone technologies already exist, including systems that analyze past data to predict and conclude some useful information for controlling the spread of COVID-19 infections using minimum resources. The AI and ML approach can be helpful to design different models to give a predictive solution for mitigating infection and preventing larger outbreaks. This book: Examines the use of artificial intelligence (AI), machine learning (ML), Internet of Things (IoT), and drone technologies as a helpful predictive solution for controlling infection of COVID-19 Covers recent research related to the COVID-19 pandemic and includes the analysis, implementation, usage, and proposed ideas and models with architecture to handle a pandemic outbreak Examines the performance, implementation, architecture, and techniques of different analytical and statistical models related to COVID-19 Includes different case studies on COVID-19 Dr. Chhabi Rani Panigrahi is Assistant Professor in the Department of Computer Science at Rama Devi Women’s University, Bhubaneswar, India. Dr. Bibudhendu Pati is Associate Professor and Head of the Department of Computer Science at Rama Devi Women’s University, Bhubaneswar, India. Dr. Mamata Rath is Assistant Professor in the School of Management (Information Technology) at Birla Global University, Bhubaneswar, India. Prof. Rajkumar Buyya is a Redmond Barry Distinguished Professor and Director of the Cloud Computing and Distributed Systems (CLOUDS) Laboratory at the University of Melbourne, Australia.
| Author | : Aboul-Ella Hassanien,Nilanjan Dey,Sally Elghamrawy |
| Publisher | : Springer Nature |
| Release Date | : 2020-11-13 |
| ISBN 10 | : 3030552586 |
| Pages | : 307 pages |
This book includes research articles and expository papers on the applications of artificial intelligence and big data analytics to battle the pandemic. In the context of COVID-19, this book focuses on how big data analytic and artificial intelligence help fight COVID-19. The book is divided into four parts. The first part discusses the forecasting and visualization of the COVID-19 data. The second part describes applications of artificial intelligence in the COVID-19 diagnosis of chest X-Ray imaging. The third part discusses the insights of artificial intelligence to stop spread of COVID-19, while the last part presents deep learning and big data analytics which help fight the COVID-19.
| Author | : Ben Waber |
| Publisher | : FT Press |
| Release Date | : 2013-04-24 |
| ISBN 10 | : 0133158330 |
| Pages | : 240 pages |
Discover powerful hidden social "levers" and networks within your company… then, use that knowledge to make slight "tweaks" that dramatically improve both business performance and employee fulfillment! In People Analytics, MIT Media Lab innovator Ben Waber shows how sensors and analytics can give you an unprecedented understanding of how your people work and collaborate, and actionable insights for building a more effective, productive, and positive organization. Through cutting-edge case studies, Waber shows how: Changing the way call center employees spent their breaks increased performance by 25% while significantly reducing stress Quantifying the failure of marketing and customer service to communicate led to a more cohesive and profitable organization Tweaking the balance of in-person and electronic communication can enhance the value of both Sensor data can help you discover who your internal experts really are Identifying employees involved in "creative" behaviors can help you promote innovation throughout your business Sensors and simulations can help you optimize your sick-day policies Measuring informal interactions can improve the chances that a merger, acquisition, or "mega-project" will succeed Drawing on his cutting-edge work at MIT and Harvard, Waber addresses crucial issues ranging from technology to privacy, revealing what will be possible in a few years, and what you can achieve right now. In bringing the power of analytics to organizational development, he offers immense new opportunities to everyone with responsibility for workplace performance.
| Author | : Gitanjali Rahul Shinde |
| Publisher | : N.A |
| Release Date | : 2020-11 |
| ISBN 10 | : 9780367564957 |
| Pages | : 329 pages |
"Epidemic trend analysis, timeline progression, prediction and recommendation are critical for initiating effective public health control strategies and AI and data analytics play an important role in epidemiology, diagnostic and clinical fronts. The focus of this book is data analytics for COVID-19 which includes an overview of COVID-19 in terms of epidemic/pandemic, data processing and knowledge extraction. Data sources, storage and platforms are discussed along with discussion on data models, their performance, different Big data techniques, tools and technologies. This book also addresses the challenges in applying analytics to pandemic scenarios, case studies and control strategies"--
Trust Creating the Foundation for Entrepreneurship in Developing Countries Entrepreneurial ventures often fail in the developing world because of the lack of something taken for granted in the developed world: trust. Over centuries the developed world has built up customs and institutions like enforceable contracts, an impartial legal system, credible regulatory bodies, even unofficial but respected sources of information like Yelp or Consumer Reports that have created a high level of what scholar and entrepreneur Tarun Khanna calls “ambient trust.” If a product is FDA-approved we feel confident it's safe. If someone makes an untrue claim or breaks an agreement we can sue. Police don't demand bribes to do their jobs. Certainly there are exceptions, but when brought to light they provoke a scandal, not a shrug. This is not the case in the developing world. But rather than become casualties of mistrust, Khanna shows that smart entrepreneurs adopt the mindset that, like it or not, it's up to them to weave their own independent web of trust—with their employees, their partners, their clients, their customers and with society as a whole. This can certainly be challenging, and requires innovative approaches in places where the level of societal mistrust is so high that, as in one example Khanna provides, an official certification of quality simply arouses suspicion—and lowers sales! Using vivid examples from Brazil, China, India, Mexico and elsewhere, Khanna shows how entrepreneurs can build on existing customs and practices instead of trying to push against them. He highlights the role new technologies can play (but cautions that these are not panaceas), and explains how entrepreneurs can find dependable partners in national and local governments to create impact at scale. As far back as the 18th century Adam Smith recognized trust as what Khanna calls “the hidden engine of economic progress.” “Frankness and openness conciliate confidence,” Smith wrote. “We trust the man who seems willing to trust us.” That kind of confidence is critical to entrepreneurial success, but in the developing world entrepreneurs have to establish it through their own efforts. As Khanna puts it, “the entrepreneur must not just create, she must create the conditions to create.”
| Author | : Jules S. Damji,Brooke Wenig,Tathagata Das,Denny Lee |
| Publisher | : O'Reilly Media |
| Release Date | : 2020-07-16 |
| ISBN 10 | : 1492050016 |
| Pages | : 400 pages |
Data is bigger, arrives faster, and comes in a variety of formats—and it all needs to be processed at scale for analytics or machine learning. But how can you process such varied workloads efficiently? Enter Apache Spark. Updated to include Spark 3.0, this second edition shows data engineers and data scientists why structure and unification in Spark matters. Specifically, this book explains how to perform simple and complex data analytics and employ machine learning algorithms. Through step-by-step walk-throughs, code snippets, and notebooks, you’ll be able to: Learn Python, SQL, Scala, or Java high-level Structured APIs Understand Spark operations and SQL Engine Inspect, tune, and debug Spark operations with Spark configurations and Spark UI Connect to data sources: JSON, Parquet, CSV, Avro, ORC, Hive, S3, or Kafka Perform analytics on batch and streaming data using Structured Streaming Build reliable data pipelines with open source Delta Lake and Spark Develop machine learning pipelines with MLlib and productionize models using MLflow
| Author | : Nigel Guenole,Jonathan Ferrar,Sheri Feinzig |
| Publisher | : FT Press |
| Release Date | : 2017-05-19 |
| ISBN 10 | : 0134544544 |
| Pages | : 352 pages |
Learn from Today’s Most Successful Workforce Analytics Leaders Transforming the immense potential of workforce analytics into reality isn’t easy. Pioneering practitioners have learned crucial lessons that can help you succeed. The Power of People shares their journeys—and their indispensable insights. Drawing on incisive case studies and vignettes, three experts help you bring purpose and clarity to any workforce analytics project, with robust research design and analysis to get reliable insights. They reveal where to start, where to find stakeholder support, and how to earn “quick wins” to build upon. You’ll learn how to sustain success through best-practice data management, technology usage, partnering, and skill building. Finally, you’ll discover how to earn even more value by establishing an analytical mindset throughout HR, and building two key skills: storytelling and visualization. The Power of People will be invaluable to HR executives establishing or leading analytics functions; HR professionals planning analytics projects; and any business executive who wants more value from HR.
| Author | : Foster Provost,Tom Fawcett |
| Publisher | : "O'Reilly Media, Inc." |
| Release Date | : 2013-07-27 |
| ISBN 10 | : 144937428X |
| Pages | : 414 pages |
Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you understand the many data-mining techniques in use today. Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making. Understand how data science fits in your organization—and how you can use it for competitive advantage Treat data as a business asset that requires careful investment if you’re to gain real value Approach business problems data-analytically, using the data-mining process to gather good data in the most appropriate way Learn general concepts for actually extracting knowledge from data Apply data science principles when interviewing data science job candidates