The Handbook of Distance Learning for Real-Time and Asynchronous Information Technology Education delves deep into the construct of real-time, asynchronous education through information technology, pooling experiences from seasoned researchers and educators to detail their past successes and failures, discussing their techniques, hardships, and triumphs in the search for innovative and effective distance learning education for IT programs. This Premier Reference Source answers the increasing demand for a fundamental, decisive source on this cutting-edge issue facing all institutions, covering topics such as asynchronous communication, real-time instruction, multimedia content, content delivery, and distance education technologies.
Mike Whitman is an Associate Professor of Information Systems in the Department of Computer Science and Information Systems at Kennesaw State University, GA. He is also the Director of the Master of Science in Information Systems and Director of the Center for Information Security Education and Awareness at Kennesaw State University, USA. Dr. Whitman received his Ph.D. in Management Information Systems, an MBA and a Bachelor’s Degree in Management from Auburn University. Dr. Whitman’s current research interests include information security, security policy, computer use ethics and IS research methods. He has published articles on these topics in journals such as Information Systems Research, Communications of the ACM, Information & Management, the Journal of International Business Systems, and the Journal of Computer Information Systems. He has delivered frequent presentations at national and regional conferences, including the Americas Conference on Information Systems, the Decision Sciences Institute and the Southern Association for Information Systems.
Amy Woszczynski is an Assistant Professor of Information Systems in the Department of Computer Science and Information Systems at Kennesaw State University. She received her Ph.D. in Industrial Management from Clemson University, her MBA from Kennesaw State University, and a Bachelor's Degree in Industrial Engineering at Georgia Tech. Dr. Woszczynski's current research interests include pedagogy and curriculum to improve the success rate of students in the first programming course, individual differences in the information systems classroom, diversity in the IT workforce, and research methods in information systems. She has published articles on these topics in journals such as Computers in Human Behavior and Industrial Management and Data Systems. She has delivered frequent presentations at national and regional conferences, including the Americas Conference on Information Systems, the Southern Association for Information Systems, and the Southeast Informs.
Herbert J. Mattord, MBA, CISM, CISSP recently completed 24 years of IT industry experience as an application developer, database administrator, project manager, and information security practitioner before joining faculty as a full time tenure-track instructor. During his career as an IT practitioner, he has been an adjunct professor at a number of universities throughout the south for over 20 years. He currently teaches courses in Information Security, Data Communications, Local Area Networks, Database Technology, Project Management, and Systems Analysis & Design. He is the co-author of Principles of Information Security, Management of Information Security, Principles of Incident Response and Disaster Recovery, Readings and Cases in the Management of Information Security, and The Hands-On Information Security Lab Manual. He was formerly the Manager of Corporate Information Technology Security at Georgia-Pacific Corporation. [Editor]
Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.
By using concrete examples, minimal theory, and two production-ready Python frameworks—scikit-learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you’ve learned, all you need is programming experience to get started.Explore the machine learning landscape, particularly neural netsUse scikit-learn to track an example machine-learning project end-to-endExplore several training models, including support vector machines, decision trees, random forests, and ensemble methodsUse the TensorFlow library to build and train neural netsDive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learningLearn techniques for training and scaling deep neural netsApply practical code examples without acquiring excessive machine learning theory or algorithm details
Artificial Intelligence helps choose what books you buy, what movies you see, and even who you date. It puts the "smart" in your smartphone and soon it will drive your car. It makes most of the trades on Wall Street, and controls vital energy, water, and transportation infrastructure. But Artificial Intelligence can also threaten our existence.
In as little as a decade, AI could match and then surpass human intelligence. Corporations and government agencies are pouring billions into achieving AI's Holy Grail—human-level intelligence. Once AI has attained it, scientists argue, it will have survival drives much like our own. We may be forced to compete with a rival more cunning, more powerful, and more alien than we can imagine.
Through profiles of tech visionaries, industry watchdogs, and groundbreaking AI systems, Our Final Invention explores the perils of the heedless pursuit of advanced AI. Until now, human intelligence has had no rival. Can we coexist with beings whose intelligence dwarfs our own? And will they allow us to?