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Books about printing written for printers or would-be printers go back over 300 years. The earliest of them were almost exclusively concerned with books; this century, however, there has been more emphasis on other kinds of documents, and particularly their design. But no shift in document production has been more sudden than the one that has happened most recently. ConSequently, the last five years have witnessed a substantial movement away from books written for professionals to ones whose aim is to help would-be authors produce their own documents. The opportunities for authors to do this have been opened up by the advent of desktop publishing (a term coined as recently as 1984). As most exponents of desktop publishing have come to realise, the term is something of a misnomer because the provision of facilities that allow authors to produce their own material for publishing is not quite the same thing as publish ing. Nevertheless, it has been useful in focussing attention on author-produced documents, and what might be described as the democratisation of document production. This book is different from others in the field. Its target audience is the busy scientist engaged in teaching or research who uses computers in the ordinary course of work. The world of scientific publishing is rapidly moving towards the day when journals will expect contributions from authors on disc, or even by direct transfer of data from the author's computer to the output device of an editor via telephone and satellite.
This book focuses on the best possible communication strategies for anyone working with data. From students developing a research poster to faculty presenting data findings at a conference, it provides the guiding principles of presenting data in evidence-based ways so that audiences are more engaged and researchers are better understood.
Computer Science: Reflections on the Field, Reflections from the Field provides a concise characterization of key ideas that lie at the core of computer science (CS) research. The book offers a description of CS research recognizing the richness and diversity of the field. It brings together two dozen essays on diverse aspects of CS research, their motivation and results. By describing in accessible form computer science's intellectual character, and by conveying a sense of its vibrancy through a set of examples, the book aims to prepare readers for what the future might hold and help to inspire CS researchers in its creation.
This volume constitutes selected papers presented at the Third International Conference on Computing and Data Science, CONF-CDS 2021, held online in August 2021. The 22 full papers 9 short papers presented in this volume were thoroughly reviewed and selected from the 85 qualified submissions. They are organized in topical sections on advances in deep learning; algorithms in machine learning and statistics; advances in natural language processing.
FOREWORD BY GUY KAWASAKI Presentation designer and internationally acclaimed communications expert Garr Reynolds, creator of the most popular Web site on presentation design and delivery on the Net — presentationzen.com — shares his experience in a provocative mix of illumination, inspiration, education, and guidance that will change the way you think about making presentations with PowerPoint or Keynote. Presentation Zen challenges the conventional wisdom of making "slide presentations" in today’s world and encourages you to think differently and more creatively about the preparation, design, and delivery of your presentations. Garr shares lessons and perspectives that draw upon practical advice from the fields of communication and business. Combining solid principles of design with the tenets of Zen simplicity, this book will help you along the path to simpler, more effective presentations.
An introduction for undergraduates to every stage of sociological research, showing how to deal effectively with typical problems they might encounter. The book is fully updated to include examples from the LA riots and the 1992 presidential elections.
Data Analysis and Presentation Skills: An Introduction for the Life and Medical Sciences is an invaluable text allowing students to develop appropriate key skills when designing experiments, generating results, analysing data and ultimately presenting findings to academics and referees. Taking a hands-on approach, each of these key areas is introduced clearly and carefully, showing how to access and evaluate information using a variety of resources. Basic analytical theory is gradually introduced alongside practical applications to enhance student understanding. The reader is shown how to present data in charts using Microsoft Excel and statistical analysis is carefully explained showing clearly how to manipulate data in spreadsheets and analyse the results using commonly used tests. A section is also included on the use of PowerPoint as well as giving advice on how to prepare a short talk or seminar. Includes numerous relevant examples and case studies drawn from the Life Sciences Guidance on how to complete and present practical and project work through to postgraduate dissertation. Clear step-by-step introduction to Microsoft Excel, presentation skills and statistical analysis. Invaluable for all students within the Life and Medical Sciences
Visualization in scientific computing is getting more and more attention from many people. Especially in relation with the fast increase of com puting power, graphic tools are required in many cases for interpreting and presenting the results of various simulations, or for analyzing physical phenomena. The Eurographics Working Group on Visualization in Scientific Com puting has therefore organized a first workshop at Electricite de France (Clamart) in cooperation with ONERA (Chatillon). A wide range of pa pers were selected in order to cover most of the topics of interest for the members of the group, for this first edition, and 26 of them were presented in two days. Subsequently 18 papers were selected for this volume. 1'he presentations were organized in eight small sessions, in addition to discussions in small subgroups. The first two sessions were dedicated to the specific needs for visualization in computational sciences: the need for graphics support in large computing centres and high performance net works, needs of research and education in universities and academic cen tres, and the need for effective and efficient ways of integrating numerical computations or experimental data and graphics. Three of those papers are in Part I of this book. The third session discussed the importance and difficulties of using stan dards in visualization software, and was related to the fourth session where some reference models and distributed graphics systems were discussed. Part II has five papers from these sessions.
This book discusses the principles and practical applications of data science, addressing key topics including data wrangling, statistics, machine learning, data visualization, natural language processing and time series analysis. Detailed investigations of techniques used in the implementation of recommendation engines and the proper selection of metrics for distance-based analysis are also covered. Utilizing numerous comprehensive code examples, figures, and tables to help clarify and illuminate essential data science topics, the authors provide an extensive treatment and analysis of real-world questions, focusing especially on the task of determining and assessing answers to these questions as expeditiously and precisely as possible. This book addresses the challenges related to uncovering the actionable insights in “big data,” leveraging database and data collection tools such as web scraping and text identification. This book is organized as 11 chapters, structured as independent treatments of the following crucial data science topics: Data gathering and acquisition techniques including data creation Managing, transforming, and organizing data to ultimately package the information into an accessible format ready for analysis Fundamentals of descriptive statistics intended to summarize and aggregate data into a few concise but meaningful measurements Inferential statistics that allow us to infer (or generalize) trends about the larger population based only on the sample portion collected and recorded Metrics that measure some quantity such as distance, similarity, or error and which are especially useful when comparing one or more data observations Recommendation engines representing a set of algorithms designed to predict (or recommend) a particular product, service, or other item of interest a user or customer wishes to buy or utilize in some manner Machine learning implementations and associated algorithms, comprising core data science technologies with many practical applications, especially predictive analytics Natural Language Processing, which expedites the parsing and comprehension of written and spoken language in an effective and accurate manner Time series analysis, techniques to examine and generate forecasts about the progress and evolution of data over time Data science provides the methodology and tools to accurately interpret an increasing volume of incoming information in order to discern patterns, evaluate trends, and make the right decisions. The results of data science analysis provide real world answers to real world questions. Professionals working on data science and business intelligence projects as well as advanced-level students and researchers focused on data science, computer science, business and mathematics programs will benefit from this book.
Why research? -- Developing research questions -- Data -- Principles of data management -- Finding and using secondary data -- Primary and administrative data -- Working with missing data -- Principles of data presentation -- Designing tables for data presentations -- Designing graphics for data presentations