Download or read book Scientific Data Analysis using Jython Scripting and Java written by Sergei V. Chekanov and published by Springer Science & Business Media. This book was released on 2010-08-05 with total page 452 pages. Available in PDF, EPUB and Kindle. Book excerpt: Scientific Data Analysis using Jython Scripting and Java presents practical approaches for data analysis using Java scripting based on Jython, a Java implementation of the Python language. The chapters essentially cover all aspects of data analysis, from arrays and histograms to clustering analysis, curve fitting, metadata and neural networks. A comprehensive coverage of data visualisation tools implemented in Java is also included. Written by the primary developer of the jHepWork data-analysis framework, the book provides a reliable and complete reference source laying the foundation for data-analysis applications using Java scripting. More than 250 code snippets (of around 10-20 lines each) written in Jython and Java, plus several real-life examples help the reader develop a genuine feeling for data analysis techniques and their programming implementation. This is the first data-analysis and data-mining book which is completely based on the Jython language, and opens doors to scripting using a fully multi-platform and multi-threaded approach. Graduate students and researchers will benefit from the information presented in this book.
Download or read book Numeric Computation and Statistical Data Analysis on the Java Platform written by Sergei V. Chekanov and published by Springer. This book was released on 2016-03-23 with total page 620 pages. Available in PDF, EPUB and Kindle. Book excerpt: Numerical computation, knowledge discovery and statistical data analysis integrated with powerful 2D and 3D graphics for visualization are the key topics of this book. The Python code examples powered by the Java platform can easily be transformed to other programming languages, such as Java, Groovy, Ruby and BeanShell. This book equips the reader with a computational platform which, unlike other statistical programs, is not limited by a single programming language. The author focuses on practical programming aspects and covers a broad range of topics, from basic introduction to the Python language on the Java platform (Jython), to descriptive statistics, symbolic calculations, neural networks, non-linear regression analysis and many other data-mining topics. He discusses how to find regularities in real-world data, how to classify data, and how to process data for knowledge discoveries. The code snippets are so short that they easily fit into single pages. Numeric Computation and Statistical Data Analysis on the Java Platform is a great choice for those who want to learn how statistical data analysis can be done using popular programming languages, who want to integrate data analysis algorithms in full-scale applications, and deploy such calculations on the web pages or computational servers regardless of their operating system. It is an excellent reference for scientific computations to solve real-world problems using a comprehensive stack of open-source Java libraries included in the DataMelt (DMelt) project and will be appreciated by many data-analysis scientists, engineers and students.
Download or read book Neural Information Processing written by Tingwen Huang and published by Springer. This book was released on 2012-11-05 with total page 730 pages. Available in PDF, EPUB and Kindle. Book excerpt: The five volume set LNCS 7663, LNCS 7664, LNCS 7665, LNCS 7666 and LNCS 7667 constitutes the proceedings of the 19th International Conference on Neural Information Processing, ICONIP 2012, held in Doha, Qatar, in November 2012. The 423 regular session papers presented were carefully reviewed and selected from numerous submissions. These papers cover all major topics of theoretical research, empirical study and applications of neural information processing research. The 5 volumes represent 5 topical sections containing articles on theoretical analysis, neural modeling, algorithms, applications, as well as simulation and synthesis.
Download or read book The Handbook On Reasoning based Intelligent Systems written by Nakamatsu Kazumi and published by World Scientific. This book was released on 2013-01-18 with total page 680 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book consists of various contributions in conjunction with the keywords “reasoning” and “intelligent systems”, which widely covers theoretical to practical aspects of intelligent systems. Therefore, it is suitable for researchers or graduate students who want to study intelligent systems generally.
Download or read book Python Scripting for Computational Science written by Hans Petter Langtangen and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 743 pages. Available in PDF, EPUB and Kindle. Book excerpt: Scripting with Python makes you productive and increases the reliability of your scientific work. Here, the author teaches you how to develop tailored, flexible, and efficient working environments built from small programs (scripts) written in Python. The focus is on examples and applications of relevance to computational science: gluing existing applications and tools, e.g. for automating simulation, data analysis, and visualization; steering simulations and computational experiments; equipping programs with graphical user interfaces; making computational Web services; creating interactive interfaces with a Maple/Matlab-like syntax to numerical applications in C/C++ or Fortran; and building flexible object-oriented programming interfaces to existing C/C++ or Fortran libraries.
Download or read book Education Research and Business Technologies written by Cristian Ciurea and published by Springer Nature. This book was released on 2023-01-01 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes high-quality research papers presented at 21st International Conference on Informatics in Economy (IE 2022), which is held in Bucharest, Romania, during May 2022. This book covers research results in business informatics and related computer science topics, such as IoT, mobile-embedded and multimedia solutions, e-society, enterprise and business solutions, databases and big data, artificial intelligence, data mining and machine learning, quantitative economics.
Download or read book Java for Data Science written by Richard M. Reese and published by Packt Publishing Ltd. This book was released on 2017-01-10 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Examine the techniques and Java tools supporting the growing field of data science About This Book Your entry ticket to the world of data science with the stability and power of Java Explore, analyse, and visualize your data effectively using easy-to-follow examples Make your Java applications more capable using machine learning Who This Book Is For This book is for Java developers who are comfortable developing applications in Java. Those who now want to enter the world of data science or wish to build intelligent applications will find this book ideal. Aspiring data scientists will also find this book very helpful. What You Will Learn Understand the nature and key concepts used in the field of data science Grasp how data is collected, cleaned, and processed Become comfortable with key data analysis techniques See specialized analysis techniques centered on machine learning Master the effective visualization of your data Work with the Java APIs and techniques used to perform data analysis In Detail Data science is concerned with extracting knowledge and insights from a wide variety of data sources to analyse patterns or predict future behaviour. It draws from a wide array of disciplines including statistics, computer science, mathematics, machine learning, and data mining. In this book, we cover the important data science concepts and how they are supported by Java, as well as the often statistically challenging techniques, to provide you with an understanding of their purpose and application. The book starts with an introduction of data science, followed by the basic data science tasks of data collection, data cleaning, data analysis, and data visualization. This is followed by a discussion of statistical techniques and more advanced topics including machine learning, neural networks, and deep learning. The next section examines the major categories of data analysis including text, visual, and audio data, followed by a discussion of resources that support parallel implementation. The final chapter illustrates an in-depth data science problem and provides a comprehensive, Java-based solution. Due to the nature of the topic, simple examples of techniques are presented early followed by a more detailed treatment later in the book. This permits a more natural introduction to the techniques and concepts presented in the book. Style and approach This book follows a tutorial approach, providing examples of each of the major concepts covered. With a step-by-step instructional style, this book covers various facets of data science and will get you up and running quickly.
Download or read book Astronomical Data Analysis Software and Systems XIV written by Patrick L. Shopbell and published by . This book was released on 2005 with total page 776 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Java Data Analysis written by John R. Hubbard and published by Packt Publishing Ltd. This book was released on 2017-09-19 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get the most out of the popular Java libraries and tools to perform efficient data analysis About This Book Get your basics right for data analysis with Java and make sense of your data through effective visualizations. Use various Java APIs and tools such as Rapidminer and WEKA for effective data analysis and machine learning. This is your companion to understanding and implementing a solid data analysis solution using Java Who This Book Is For If you are a student or Java developer or a budding data scientist who wishes to learn the fundamentals of data analysis and learn to perform data analysis with Java, this book is for you. Some familiarity with elementary statistics and relational databases will be helpful but is not mandatory, to get the most out of this book. A firm understanding of Java is required. What You Will Learn Develop Java programs that analyze data sets of nearly any size, including text Implement important machine learning algorithms such as regression, classification, and clustering Interface with and apply standard open source Java libraries and APIs to analyze and visualize data Process data from both relational and non-relational databases and from time-series data Employ Java tools to visualize data in various forms Understand multimedia data analysis algorithms and implement them in Java. In Detail Data analysis is a process of inspecting, cleansing, transforming, and modeling data with the aim of discovering useful information. Java is one of the most popular languages to perform your data analysis tasks. This book will help you learn the tools and techniques in Java to conduct data analysis without any hassle. After getting a quick overview of what data science is and the steps involved in the process, you'll learn the statistical data analysis techniques and implement them using the popular Java APIs and libraries. Through practical examples, you will also learn the machine learning concepts such as classification and regression. In the process, you'll familiarize yourself with tools such as Rapidminer and WEKA and see how these Java-based tools can be used effectively for analysis. You will also learn how to analyze text and other types of multimedia. Learn to work with relational, NoSQL, and time-series data. This book will also show you how you can utilize different Java-based libraries to create insightful and easy to understand plots and graphs. By the end of this book, you will have a solid understanding of the various data analysis techniques, and how to implement them using Java. Style and approach The book takes a very comprehensive approach to enhance your understanding of data analysis. Sufficient real-world examples and use cases are included to help you grasp the concepts quickly and apply them easily in your day-to-day work. Packed with clear, easy-to-follow examples, this book will turn you into an ace data analyst in no time.
Download or read book Mathematical Software ICMS 2014 written by Hoon Hong and published by Springer. This book was released on 2014-08-01 with total page 762 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 4th International Conference on Mathematical Software, ICMS 2014, held in Seoul, South Korea, in August 2014. The 108 papers included in this volume were carefully reviewed and selected from 150 submissions. The papers are organized in topical sections named: invited; exploration; group; coding; topology; algebraic; geometry; surfaces; reasoning; special; Groebner; triangular; parametric; interfaces and general.
Download or read book Correspondence Analysis and Data Coding with Java and R written by Fionn Murtagh and published by CRC Press. This book was released on 2005-05-26 with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt: Developed by Jean-Paul Benzerci more than 30 years ago, correspondence analysis as a framework for analyzing data quickly found widespread popularity in Europe. The topicality and importance of correspondence analysis continue, and with the tremendous computing power now available and new fields of application emerging, its significance is greater
Download or read book Practical Data Science with Hadoop and Spark written by Ofer Mendelevitch and published by Addison-Wesley Professional. This book was released on 2016-12-08 with total page 463 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Complete Guide to Data Science with Hadoop—For Technical Professionals, Businesspeople, and Students Demand is soaring for professionals who can solve real data science problems with Hadoop and Spark. Practical Data Science with Hadoop® and Spark is your complete guide to doing just that. Drawing on immense experience with Hadoop and big data, three leading experts bring together everything you need: high-level concepts, deep-dive techniques, real-world use cases, practical applications, and hands-on tutorials. The authors introduce the essentials of data science and the modern Hadoop ecosystem, explaining how Hadoop and Spark have evolved into an effective platform for solving data science problems at scale. In addition to comprehensive application coverage, the authors also provide useful guidance on the important steps of data ingestion, data munging, and visualization. Once the groundwork is in place, the authors focus on specific applications, including machine learning, predictive modeling for sentiment analysis, clustering for document analysis, anomaly detection, and natural language processing (NLP). This guide provides a strong technical foundation for those who want to do practical data science, and also presents business-driven guidance on how to apply Hadoop and Spark to optimize ROI of data science initiatives. Learn What data science is, how it has evolved, and how to plan a data science career How data volume, variety, and velocity shape data science use cases Hadoop and its ecosystem, including HDFS, MapReduce, YARN, and Spark Data importation with Hive and Spark Data quality, preprocessing, preparation, and modeling Visualization: surfacing insights from huge data sets Machine learning: classification, regression, clustering, and anomaly detection Algorithms and Hadoop tools for predictive modeling Cluster analysis and similarity functions Large-scale anomaly detection NLP: applying data science to human language
Download or read book New Scientist and Science Journal written by and published by . This book was released on 2005 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Massively Multi Agent Technology written by Nadeem Jamali and published by Springer. This book was released on 2008-08-17 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the proliferation of consumer devices, computation is becoming truly ubiq- tous. Multi-agent systems hold the promise to enable utilization of these compu- tional resources for ground-breaking new applications. However, as the number of agents involved in multi-agent computations rises, traditional approaches of bui- ing multi-agent systems fail to scale. Massively multi-agent systems address this challenge of scale. Massive, in this context, is meant to capture the complexity of such systems, which precludes decision making to focus on individual agents. Agents making decisions have to reduce the complexity of the space in which they must decide. The focus, therefore, is on the approaches to manage the compl- ity, implications of this abstraction, as well as on identifying ways of applying the paradigm to problems. Papers appearing in this volume have been selected from three inter- tional workshops held in conjunction with the International Conferences on - tonomous Agents and Multiagent Systems (AAMAS) held in 2006 and 2007: First International Workshop on Coordination and Control in Massively Mul- agent Systems (CCMMS 2007); and the jointly held Second International Workshop on Massively Multi-agent Systems (MMAS 2006) and the Third Int- national Workshop on Challenges in the Coordination of Large-Scale Multi-agent Systems (LSMAS 2006).
Download or read book Web Microanalysis of Big Image Data written by Peter Bajcsy and published by Springer. This book was released on 2018-01-22 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book looks at the increasing interest in running microscopy processing algorithms on big image data by presenting the theoretical and architectural underpinnings of a web image processing pipeline (WIPP). Software-based methods and infrastructure components for processing big data microscopy experiments are presented to demonstrate how information processing of repetitive, laborious and tedious analysis can be automated with a user-friendly system. Interactions of web system components and their impact on computational scalability, provenance information gathering, interactive display, and computing are explained in a top-down presentation of technical details. Web Microanalysis of Big Image Data includes descriptions of WIPP functionalities, use cases, and components of the web software system (web server and client architecture, algorithms, and hardware-software dependencies). The book comes with test image collections and a web software system to increase the reader's understanding and to provide practical tools for conducting big image experiments. By providing educational materials and software tools at the intersection of microscopy image analyses and computational science, graduate students, postdoctoral students, and scientists will benefit from the practical experiences, as well as theoretical insights. Furthermore, the book provides software and test data, empowering students and scientists with tools to make discoveries with higher statistical significance. Once they become familiar with the web image processing components, they can extend and re-purpose the existing software to new types of analyses. Each chapter follows a top-down presentation, starting with a short introduction and a classification of related methods. Next, a description of the specific method used in accompanying software is presented. For several topics, examples of how the specific method is applied to a dataset (parameters, RAM requirements, CPU efficiency) are shown. Some tips are provided as practical suggestions to improve accuracy or computational performance.
Download or read book Astronomical Data Analysis Software and Systems XV written by Carlos Gabriel and published by . This book was released on 2006 with total page 848 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Python for Bioinformatics written by Sebastian Bassi and published by CRC Press. This book was released on 2016-04-19 with total page 612 pages. Available in PDF, EPUB and Kindle. Book excerpt: Programming knowledge is often necessary for finding a solution to a biological problem. Based on the author’s experience working for an agricultural biotechnology company, Python for Bioinformatics helps scientists solve their biological problems by helping them understand the basics of programming. Requiring no prior knowledge of programming-related concepts, the book focuses on the easy-to-use, yet powerful, Python computer language. The book begins with a very basic introduction that teaches the principles of programming. It then introduces the Biopython package, which can be useful in solving life science problems. The next section covers sophisticated tools for bioinformatics, including relational database management systems and XML. The last part illustrates applications with source code, such as sequence manipulation, filtering vector contamination, calculating DNA melting temperature, parsing a genbank file, inferring splicing sites, and more. The appendices provide a wealth of supplementary information, including instructions for installing Python and Biopython and a Python language and style guide. By incorporating examples in biology as well as code fragments throughout, the author places a special emphasis on practice, encouraging readers to experiment with the code. He shows how to use Python and the Biopython package for building web applications, genomic annotation, data manipulation, and countless other applications.
