Presenting interdisciplinary research at the forefront of present advances in information technologies and their foundations, Scientific Applications of Language Methods is a multi-author volume containing pieces of work (either original research or surveys) exemplifying the application of formal language tools in several fields, including logic and discrete mathematics, natural language processing, artificial intelligence, natural computing and bioinformatics.
This volume addresses all current aspects of relational methods and their applications in computer science. It presents a broad variety of fields and issues in which theories of relations provide conceptual or technical tools. The contributions address such subjects as relational methods in programming, relational constraints, relational methods in linguistics and spatial reasoning, relational modelling of uncertainty. All contributions provide the readers with new and original developments in the respective fields. The reader thus gets an interdisciplinary spectrum of the state of the art of relational methods and implementation-oriented solutions of problems related to these areas.
Would you like to gather big datasets, analyze them, and visualize the results, all in one program? If this describes you, then Introduction to Python Programming for Business and Social Science Applications is the book for you. Authors Frederick Kaefer and Paul Kaefer walk you through each step of the Python package installation and analysis process, with frequent exercises throughout so you can immediately try out the functions you’ve learned. Written in straightforward language for those with no programming background, this book will teach you how to use Python for your research and data analysis. Instead of teaching you the principles and practices of programming as a whole, this application-oriented text focuses on only what you need to know to research and answer social science questions. The text features two types of examples, one set from the General Social Survey and one set from a large taxi trip dataset from a major metropolitan area, to help readers understand the possibilities of working with Python. Chapters on installing and working within a programming environment, basic skills, and necessary commands will get you up and running quickly, while chapters on programming logic, data input and output, and data frames help you establish the basic framework for conducting analyses. Further chapters on web scraping, statistical analysis, machine learning, and data visualization help you apply your skills to your research. More advanced information on developing graphical user interfaces (GUIs) help you create functional data products using Python to inform general users of data who don’t work within Python. First there was IBM® SPSS®, then there was R, and now there′s Python. Statistical software is getting more aggressive - let authors Frederick Kaefer and Paul Kaefer help you tame it with Introduction to Python Programming for Business and Social Science Applications.
This book encloses latest and advanced researches on artificial intelligence and its applications in computer science. It is an interesting book that aims to help students, researchers, industrialists, and policymakers understand, promote, and synthesize innovative solutions and think of new ideas with the application of artificial intelligence concepts. It also allows to know the existing scientific works and contributions in the literature. This book identifies original research in new directions and advances focused on multidisciplinary areas and closely related to the use of artificial intelligence in applications of computer science, communication, and technology. The present book contains selected and extended high-quality papers of the 1st international conference on Machine Intelligence and Computer Science Applications (ICMICSA’2022). It is the result of a reviewed, evaluated, and presented work in ICMICSA’2022 held on November 28–29, 2022, in Khouribga, Morocco.
This book constitutes the thoroughly refereed papers of the 16th International Conference on Implementation and Application of Automata, CIAA 2011, held in Blois, France, in July 2011. The 20 revised full papers together with 4 short papers were carefully selected from 38 submissions. The papers cover various topics such as applications of automata in computer-aided verification; natural language processing; pattern matching, data storage and retrieval; document engineering and bioinformatics as well as foundational work on automata theory.
The fast and easy way to learn Python programming and statistics Python is a general-purpose programming language created in the late 1980s—and named after Monty Python—that's used by thousands of people to do things from testing microchips at Intel, to powering Instagram, to building video games with the PyGame library. Python For Data Science For Dummies is written for people who are new to data analysis, and discusses the basics of Python data analysis programming and statistics. The book also discusses Google Colab, which makes it possible to write Python code in the cloud. Get started with data science and Python Visualize information Wrangle data Learn from data The book provides the statistical background needed to get started in data science programming, including probability, random distributions, hypothesis testing, confidence intervals, and building regression models for prediction.
This book is a compilation of peer-reviewed papers presented at the International Conference on Machine Intelligence and Data Science Applications, organized by the School of Computer Science, University of Petroleum & Energy Studies, Dehradun, on September 4 and 5, 2020. The book starts by addressing the algorithmic aspect of machine intelligence which includes the framework and optimization of various states of algorithms. Variety of papers related to wide applications in various fields like image processing, natural language processing, computer vision, sentiment analysis, and speech and gesture analysis have been included with upfront details. The book concludes with interdisciplinary applications like legal, health care, smart society, cyber physical system and smart agriculture. The book is a good reference for computer science engineers, lecturers/researchers in machine intelligence discipline and engineering graduates.
This book constitutes the thoroughly refereed joint postproceedings of the 8th International Seminar on Relational Methods in Computer Science, the 3rd International Workshop on Applications of Kleene Algebra, and the Workshop of COST Action 274. The 17 revised full papers presented together with 3 invited papers address foundational and methodological aspects of the calculi of relations and Kleene algebra, and their application in various areas of computer science and information processing.
