KNIME Essentials is a practical guide aimed at getting the results you want, as quickly as possible."Knime Essentials" is written for data analysts looking to quickly get up to speed using the market leader in data processing tools, KNIME.
Author: Gábor Bakos
Publisher: Packt Publishing Ltd
KNIME Essentials is a practical guide aimed at getting the results you want, as quickly as possible."Knime Essentials" is written for data analysts looking to quickly get up to speed using the market leader in data processing tools, KNIME. No knowledge of KNIME is required, but we will assume that you have some background in data processing.
He wrote the book KNIME Essentials. He has contributions to KNIME, created the
RapidMiner Integration for KNIME and some other KNIME plugins: Vega, HiTS.
He was the co-author of the article “Workflow-Based Software Environment For ...
Author: Azevedo, Ana
Publisher: IGI Global
Uncovering and analyzing data associated with the current business environment is essential in maintaining a competitive edge. As such, making informed decisions based on this data is crucial to managers across industries. Integration of Data Mining in Business Intelligence Systems investigates the incorporation of data mining into business technologies used in the decision making process. Emphasizing cutting-edge research and relevant concepts in data discovery and analysis, this book is a comprehensive reference source for policymakers, academicians, researchers, students, technology developers, and professionals interested in the application of data mining techniques and practices in business information systems.
KNIME (the K-word is silent, such that it's pronounced nīm) is a top-rated platform
for data analytics with broad applications ... In this chapter, we're going to be
walking you through some essentials of KNIME, and how it can be used to
Author: William Vance
Discover advanced methods and strategies to learn data science for business. When the concept ‘data science’ was incorporated into some basic business decision processes, it was, at some point, neglected. But with the recent technological advancement, this method of analytics can no longer be neglected in the various decision-making process of a business. Yet, a lot of business owners are unaware of the ubiquity of data opportunities in business The book introduces various methods and strategies that are essential to facilitate your learning path into data science and how it can be used for business decisions and organizational growth. In simple terms, it provides real-world situations that can be used to explain the pervasiveness of data opportunities in business. Hence, as a business owner, you can learn how to participate smartly on your data science project even without the help of a data scientist. You will also discover advanced methods and strategies on how to think analytically while using various data mining strategies to collate data for your analysis. In this book, you will learn how to wrangle, program, explore data sets, model your data, and how to communicate business decisions and findings using data visualization techniques. While this book is a comprehensive guide on various method methods and strategies to learn data science for business, it doesn’t include the general basic knowledge of data science. Hence, the following are some of the things you should expect: · The pervasiveness of data opportunities · The overall process of business decisions and how data science is useful during this process · Various analytical approaches to business · Programming languages · And data visualization Finally, the opportunities that big data provides are vast; let this book help you harness those opportunities. Now is the time to start collating essential information, making rational predictions, and gaining a competitive advantage over other businesses using the vast array of data available online.
G. Bakos, KNIME Essentials (Packt Publishing, 2013) R. Banker, Maximum
likelihood, consistency and data envelopment analysis: a statistical foundation.
Manag. Sci. 39(10), 1265–1273 (1993) A.L. Barabasi, R. Albert, Emergence of
Author: Marina Resta
The book focuses on a set of cutting-edge research techniques, highlighting the potential of soft computing tools in the analysis of economic and financial phenomena and in providing support for the decision-making process. In the first part the textbook presents a comprehensive and self-contained introduction to the field of self-organizing maps, elastic maps and social network analysis tools and provides necessary background material on the topic, including a discussion of more recent developments in the field. In the second part the focus is on practical applications, with particular attention paid to budgeting problems, market simulations, and decision-making processes, and on how such problems can be effectively managed by developing proper methods to automatically detect certain patterns. The book offers a valuable resource for both students and practitioners with an introductory-level college math background.
Using KNIME for environmental good stewardship Everyone knows that energy
usage predictions and audits are essential to responsible energy planning.
Within KNIME, you use time series analysis and autoregressive modeling to
Author: Lillian Pierson
Publisher: John Wiley & Sons
Discover how data science can help you gain in-depth insight into your business - the easy way! Jobs in data science abound, but few people have the data science skills needed to fill these increasingly important roles. Data Science For Dummies is the perfect starting point for IT professionals and students who want a quick primer on all areas of the expansive data science space. With a focus on business cases, the book explores topics in big data, data science, and data engineering, and how these three areas are combined to produce tremendous value. If you want to pick-up the skills you need to begin a new career or initiate a new project, reading this book will help you understand what technologies, programming languages, and mathematical methods on which to focus. While this book serves as a wildly fantastic guide through the broad, sometimes intimidating field of big data and data science, it is not an instruction manual for hands-on implementation. Here’s what to expect: Provides a background in big data and data engineering before moving on to data science and how it's applied to generate value Includes coverage of big data frameworks like Hadoop, MapReduce, Spark, MPP platforms, and NoSQL Explains machine learning and many of its algorithms as well as artificial intelligence and the evolution of the Internet of Things Details data visualization techniques that can be used to showcase, summarize, and communicate the data insights you generate It's a big, big data world out there—let Data Science For Dummies help you harness its power and gain a competitive edge for your organization.
Substantially updating the previous edition, then entitled Guide to Intelligent Data Analysis, this core textbook continues to provide a hands-on instructional approach to many data science techniques, and explains how these are used to ...
- Tariq Rashid hat eine besondere Fähigkeit, schwierige Konzepte verständlich zu erklären, dadurch werden Neuronale Netze für jeden Interessierten zugänglich und praktisch nachvollziehbar.
Author: Tariq Rashid
Neuronale Netze sind Schlüsselelemente des Deep Learning und der Künstlichen Intelligenz, die heute zu Erstaunlichem in der Lage sind. Dennoch verstehen nur wenige, wie Neuronale Netze tatsächlich funktionieren. Dieses Buch nimmt Sie mit auf eine unterhaltsame Reise, die mit ganz einfachen Ideen beginnt und Ihnen Schritt für Schritt zeigt, wie Neuronale Netze arbeiten. Dafür brauchen Sie keine tieferen Mathematik-Kenntnisse, denn alle mathematischen Konzepte werden behutsam und mit vielen Illustrationen erläutert. Dann geht es in die Praxis: Sie programmieren Ihr eigenes Neuronales Netz mit Python und bringen ihm bei, handgeschriebene Zahlen zu erkennen, bis es eine Performance wie ein professionell entwickeltes Netz erreicht. Zum Schluss lassen Sie das Netz noch auf einem Raspberry Pi Zero laufen. - Tariq Rashid hat eine besondere Fähigkeit, schwierige Konzepte verständlich zu erklären, dadurch werden Neuronale Netze für jeden Interessierten zugänglich und praktisch nachvollziehbar.
Guide to Intelligent Data Analysis provides a hands-on instructional approach to many basic data analysis techniques, and explains how these are used to solve data analysis problems.
Author: Michael R. Berthold
Publisher: Springer Science & Business Media
Each passing year bears witness to the development of ever more powerful computers, increasingly fast and cheap storage media, and even higher bandwidth data connections. This makes it easy to believe that we can now – at least in principle – solve any problem we are faced with so long as we only have enough data. Yet this is not the case. Although large databases allow us to retrieve many different single pieces of information and to compute simple aggregations, general patterns and regularities often go undetected. Furthermore, it is exactly these patterns, regularities and trends that are often most valuable. To avoid the danger of “drowning in information, but starving for knowledge” the branch of research known as data analysis has emerged, and a considerable number of methods and software tools have been developed. However, it is not these tools alone but the intelligent application of human intuition in combination with computational power, of sound background knowledge with computer-aided modeling, and of critical reflection with convenient automatic model construction, that results in successful intelligent data analysis projects. Guide to Intelligent Data Analysis provides a hands-on instructional approach to many basic data analysis techniques, and explains how these are used to solve data analysis problems. Topics and features: guides the reader through the process of data analysis, following the interdependent steps of project understanding, data understanding, data preparation, modeling, and deployment and monitoring; equips the reader with the necessary information in order to obtain hands-on experience of the topics under discussion; provides a review of the basics of classical statistics that support and justify many data analysis methods, and a glossary of statistical terms; includes numerous examples using R and KNIME, together with appendices introducing the open source software; integrates illustrations and case-study-style examples to support pedagogical exposition. This practical and systematic textbook/reference for graduate and advanced undergraduate students is also essential reading for all professionals who face data analysis problems. Moreover, it is a book to be used following one’s exploration of it. Dr. Michael R. Berthold is Nycomed-Professor of Bioinformatics and Information Mining at the University of Konstanz, Germany. Dr. Christian Borgelt is Principal Researcher at the Intelligent Data Analysis and Graphical Models Research Unit of the European Centre for Soft Computing, Spain. Dr. Frank Höppner is Professor of Information Systems at Ostfalia University of Applied Sciences, Germany. Dr. Frank Klawonn is a Professor in the Department of Computer Science and Head of the Data Analysis and Pattern Recognition Laboratory at Ostfalia University of Applied Sciences, Germany. He is also Head of the Bioinformatics and Statistics group at the Helmholtz Centre for Infection Research, Braunschweig, Germany.
The entire InfoChem mining process shown in the very first diagram is
implemented in a KNIME workflow . ... the automated annotation of thousands of
screening hits in batch is becoming feasible and has the potential to play an essential role ...
Lastly, in the course of this work we developed an open source automated cell tracking and segmentation workflow designed in conjunction with the Konstanz Information Miner (KNIME) analytics platform and ImageJ/FIJI plugins.
Author: Edward Leandus Evans
The human immunodeficiency virus type 1 (HIV-1) remains a significant social and economic burden with >36 million people globally living with the virus. HIV-1 infection is cytotoxic to host cells through several known mechanisms such as syncytia formation, pyroptosis and cell cycle arrest. These viral activities ultimately lead to the development of acquired immunodeficiency syndrome (AIDS) by progressive depletion of CD4+ T-cells, leaving the host susceptible to a wide range of opportunistic bacterial, fungal and viral infections. After the discovery of HIV in the 1980s, several attempts were made to develop a non-human small animal model to study HIV-1 pathogenesis. Cells derived from mice and other rodents, however, exhibit profound blocks to HIV-1 virion production at several steps during the viral life cycle. In this dissertation, I present my research investigating species-specific, virus-host incompatibilities in rodent cells - as well as other non-human cell lines - and HIV-induced cell cycle arrest. Rodent cells are naturally resistant to HIV-1 virion production due to species-specific incompatibilities between viral Tat and Rev proteins and essential host factors CCNT1 and XPO1 (also known as CRM1) respectively. Whether these factors represent the final barriers to HIV's post-integration stages in rodent cells is unknown. By investigating HIV-1 viral gene expression in transgenic mouse cells engineered to express HIV-1 compatible CCNT1 and XPO1, we found both Rev-independent and Rev-dependent viral gene expression was supported, as well as robust viral particle production. These data support the notion that both CCNT1 and XPO1 represent the predominant blocks to efficient viral gene expression in rodent cells, which may aid in the development of a small animal model of HIV-1. We also identified a novel species-specific block to HIV-induced cell cycle arrest that we mapped to the viral protein Vif. How rodent cells resist HIV-induced cell cycle arrest is unknown. HIV-1 encodes the Vif and Vpr proteins, which are known to induce cell cycle arrest and eventually cell death. In the course of investigating the mouse resistance to HIV-induce cell cycle arrest, we discovered a profound metaphase arrest attributable to Vif expression. Vif-expressing cells traffic normally though the cell cycle prior to (1) arresting in metaphase, (2) onset of cohesion fatigue, (3) amplification of mitotic spindle pole ends and centrosomes and (4) cell death via apoptosis. Treating Vif-arrested cells with the MPS1 inhibitor reversine - thereby bypassing the spindle assembly checkpoint - releases the cells from metaphase arrest. Here we put forth evidence that Vif induces cell cycle arrest, at least in part, by dysregulating kinetochore proteins and triggering a spindle assembly checkpoint. Lastly, in the course of this work we developed an open source automated cell tracking and segmentation workflow designed in conjunction with the Konstanz Information Miner (KNIME) analytics platform and ImageJ/FIJI plugins. This automated tool has enabled single-cell analysis of live cell video microscopy data and fixed cell images by segmenting and measuring the nuclear and cytoplasmic compartments over time.