This book focuses on the integration of intelligent communication systems, control systems and devices related to all aspects of engineering and sciences. It includes high-quality research papers from the 4th International Conference on Intelligent Communication, Control and Devices (ICICCD 2020), organized by the Department of Electronics, Instrumentation and Control Engineering at the University of Petroleum and Energy Studies, Dehradun, India during 27–28 November 2020. The topics covered are a range of recent advances in intelligent communication, intelligent control, and intelligent devices.

This book covers different machine learning techniques such as artificial neural network, support vector machine, rough set theory and deep learning. It points out the difference between the techniques and their suitability for specific applications. This book also describes different applications of machine learning techniques for industrial problems. The book includes several case studies, helping researchers in academia and industries aspiring to use machine learning for solving practical industrial problems.

This book is a greatly supplemented translation from Portuguese, originally published in 2015. It discusses the most appropriate ways to create databases for research on history and other humanities, including an extensive debate about the usages that historians have made of computing since the 1950s. It has four chapters: the first is dedicated to theoretical and methodical questions about the usage of databases in history; the second is about technical issues; the third presents the concept of research engineering (how to improve research in groups); the last is about the construction of databases. The author states that the use of technology in research in history and humanities should be preceded and mediated by theories and methods which deal with these disciplines and not by technical issues. The historian must know how to think “correctly” in order to use the technological tools in an autonomous way. The book provides a background, demonstrating how theory, methodology, and technique are always articulated in historical research, and will appeal to history students and researchers.

Access is your, comprehensive reference to the world's most popular database management tool. With clear guidance toward everything from the basics to the advanced, this go-to reference helps you take advantage of everything Access 2016 has to offer. Whether you're new to Access or getting started with Access, you'll find everything you need to know to create the database solution perfectly tailored to your needs, with expert guidance every step of the way. The companion website features all examples and databases used in the book, plus trial software and a special offer from Database Creations. Start from the beginning for a complete tutorial, or dip in and grab what you need when you need it.

Your one stop guide to automating infrastructure security using DevOps and DevSecOps

Why Python?
Python is the easiest to learn and once you have a good grounding in it, you can move on to another, more complicated language. Python is a beautiful computer language. It is simple, and it is intuitive. Python is used by a sorts of people – data scientists use it for much of their number crunching and analytics; security testers use it for testing out security and IT attacks; it is used to develop high-quality web applications and many of the large applications that you use on the internet are also written in Python, including YouTube, DropBox, and Instagram.
Are you interested in learning Python? Then settle in and learn the basics in just 7 days - enough for you to be comfortable in moving on to the next level without any trouble.

If you want to increase Tableau's value to your organization, this practical book has your back. Authors Ann Jackson and Luke Stanke guide data analysts through strategies for solving real-world analytics problems using Tableau. Starting with the basics and building toward advanced topics such as multidimensional analysis and user experience, you'll explore pragmatic and creative examples that you can apply to your own data.

Machine learning is a computer programming technique in which software is built in such a way that it can learn new facts from itself and make decisions on its own when necessary. Machine learning (ML) is a large discipline, and this book covers a lot of ground. We attempted to cover all aspects of the subject. This book is designed for students enrolled in MCA, M.Sc. CS/IT, M.S., M. Tech, B.Tech , B.E. CS/IT, B.Sc. CS and BCA programs. The most notable characteristic of this book is that each chapter is taught in a straightforward manner so that the student can grasp the subject. Due to space limits, we have included a number of related ideas and tasks for the benefit of both students and teachers.
Despite our best efforts, there may be some inaccuracies. If some readers bring these to my attention, we will be grateful. Suggestions and criticisms for the book's enhancement would be warmly received.

The DevOps movement has transformed the way modern tech companies work. Amazon Web Services (AWS), which has been at the forefront of the cloud computing revolution, has also been a key contributor to the DevOps movement, creating a huge range of managed services that help you implement DevOps principles.

Do you have any of the iPhone X series devices OR you intend getting one anytime soon?