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الصفحة 12
Deep Learning with PyTorch Lightning : Build and train high-performance artificial intelligence and self-supervised models using Python
You’ll learn how to configure PyTorch Lightning on a cloud platform, understand the architectural components, and explore how they are configured to build various industry solutions. You’ll build a neural network architecture, deploy an application from scratch, and see how you can expand it based on your specific needs, beyond what the framework can provide. In the later chapters, you’ll also learn how to implement capabilities to build and train various models like Convolutional Neural Nets (CNN), Natural Language Processing (NLP), Time Series, Self-Supervised Learning, Semi-Supervised Learning, Generative Adversarial Network (GAN) using PyTorch Lightning.
Decision Support for Global Enterprises
Decision Support for Global Enterprises consists of peer-reviewed and invited papers with two primary goals: (1) Stimulate creative discussion between academic researchers and the practitioner IS community to improve the research and practice in the area. (2) Increase awareness of the problems and challenges faced by global enterprises that can be met with innovative decision support systems. Limitations are also explored, covering the following topics: the emerging enterprise decision making processes and technologies; decision making in uncertain, changing conditions; the changing infrastructure in organizations and society; the expanding role of web technologies; and emerging theories and practices for managing knowledge and making decisions.
Databases in Networked Information Systems ; 5th International Workshop, DNIS 2007, Aizu-Wakamatsu, Japan, October 17-19, 2007, Proceedings
This book Is focusing on data semantics and infrastructure for information management and interchange, the papers are organized in topical sections on geospatial decision-making, Web data management systems, infrastructure of networked information systems, and Web query and web mining systems.
Database Systems for Advanced Applications ; Vol. 3882 ; 11th International Conference, DASFAA 2006, Singapore, April 12-15, 2006, Proceedings
This book constitutes the refereed proceedings of the 11th International Conference on Database Systems for Advanced Applications, DASFAA 2006, held in Singapore in April 2006.
Database systems for advanced applications ; Vol. 3453 ; 10th international conference, DASFAA 2005, Beijing, China, April 17-20, 2005, Proceedings
Data Stream Mining and Resource Adaptive Computation.- Purpose Based Access Control for Privacy Protection in Database Systems.- Complex Networks and Network Data Mining.- Bioinformatics.- Indexing DNA Sequences Using q-Grams.- PADS: Protein Structure Alignment Using Directional Shape Signatures.- LinkageTracker: A Discriminative Pattern Tracking Approach to Linkage Disequilibrium Mapping.- Watermarking and Encryption.- Query Optimization in Encrypted Database Systems.- Watermarking Spatial Trajectory Database.- Effective Approaches for Watermarking XML Data.- XML Query Processing.- A Unifying Framework for Merging and Evaluating XML Information.- Efficient Evaluation of Partial Match Queries for XML Documents Using Information Retrieval Techniques.- PathStack: A Holistic Path Join Algorithm for Path Query with Not-Predicates on XML Data.- XML Coding and Metadata Management.- An Improved Prefix Labeling Scheme: A Binary String Approach for Dynamic Ordered XML.- Efficiently Coding and Indexing XML Document.- XQuery-Based TV-Anytime Metadata Management.- Data Mining.- Effective Database Transformation and Efficient Support Computation for Mining Sequential Patterns.
Database performance at scale: a practical guide
Optimizing database performance at the scale required for today’s data-intensive applications often requires more than performance tuning and scaling out. This book shares commonly overlooked considerations, pitfalls, and opportunities that have helped many teams break through database performance plateaus. It’s neither a definitive guide to distributed databases nor a beginner’s resource. Rather, it’s a look at the many different factors that impact performance, and our top field-tested recommendations for navigating them. Chapter 1 provides two (fun and fanciful) tales that surface some of the many roadblocks you might face and highlight the range of strategies for navigating around them.
Database and XMLTechnologies ; 5th International XML Database Symposium, XSym 2007, Vienna, Austria, September 23-24, 2007, Proceedings
This book discuss the use of and synergy between databases and XML. It provided theory and practice of XML data management and its applications. This volume also contains current research in XPath and XQuery processing, XML Updates, Temporal XML and Constraints.
Data Warehousing and Data Mining Techniques for Cyber Security
It provide techniques for collecting information from distributed databases and for performing data analysis. The ever expanding, tremendous amount of data collected and stored in large databases has far exceeded our human ability to comprehend--without the proper tools. There is a critical need for data analysis that can automatically analyze data, summarize it and predict future trends. In the modern age of Internet connectivity, concerns about denial of service attacks, computer viruses and worms are extremely important. Data Warehousing and Data Mining Techniques for Cyber Security contributes to the discipline of security informatics. The author discusses topics that intersect cyber security and data mining, while providing techniques for improving cyber security. Since the cost of information processing and internet accessibility is dropping, an increasing number of organizations are becoming vulnerable to cyber attacks. This volume introduces techniques for applications in the area of retail, finance, and bioinformatics, to name a few.
Data science in theory and practice : Techniques for big data analytics and complex data sets
Delivers a comprehensive treatment of the mathematical and statistical models useful for analyzing data sets arising in various disciplines, like banking, finance, health care, bioinformatics, security, education, and social services. Written in five parts, the book examines some of the most commonly used and fundamental mathematical and statistical concepts that form the basis of data science. The authors go on to analyze various data transformation techniques useful for extracting information from raw data, long memory behavior, and predictive modeling. Readers will also learn from topics like: Analyses of foundational theoretical subjects, including the history of data science, matrix algebra and random vectors, and multivariate analysis A comprehensive examination of time series forecasting, including the different components of time series and transformations to achieve stationarity Introductions to both the R and Python programming languages, including basic data types and sample manipulations for both languages An exploration of algorithms, including how to write one and how to perform an asymptotic analysis A comprehensive discussion of several techniques for analyzing and predicting complex data sets
Data Mining : A Knowledge Discovery Approach
This book on data mining details the unique steps of the knowledge discovery process that prescribe the sequence in which data mining projects should be performed. Data Mining offers an authoritative treatment of all development phases from problem and data understanding through data preprocessing to deployment of the results. This knowledge discovery approach is what distinguishes this book from other texts in the area. It concentrates on data preparation, clustering and association rule learning (required for processing unsupervised data), decision trees, rule induction algorithms, neural networks, and many other data mining methods, focusing predominantly on those which have proven successful in data mining projects.
Data Management. Data, Data Everywhere ; 24th British National Conference on Databases, BNCOD 24, Glasgow, UK, July 3-5, 2007, Proceedings
One of the most pressing challenges is to ?nd ways of evolving database technology to cope with its new role in underpinning the massively distributed and heterogeneous applications built on top of the Internet. This has afiected both the ways in which data has been accessed and the ways in which it is represented, with XML data management becoming an important issue and, as such, heavily represented at this conference. It has also brought back issues of performance that might have been considered largely solved by the improvements in hardware, since data now has to be managed on devices of low power and small memory as well as on standard client and powerful server machines. We therefore invited papers on all aspects of data management, particularly related to how dataisused in the ubiquitous environment of the modern Internet by complex distributed and scientific applications.
Data Management in Grids ; 1st VLDB Workshop, DMG 2005, Trondheim, Norway, September 2-3, 2005, Revised Selected Papers
This book constitutes the thoroughly refereed post-proceedings of the First International Workshop on Data Management in Grids, DMG 2005, held in Trondheim, Norway in September 2005 in conjunction with VLDB 2005. papers address all current research activities in relation to data management in dynamic, heterogeneous and cross-organizational environments, i.e. grids. They show unique expertise in the management of very large, widely distributed databases.
Data center networking : Network topologies and traffic management in large-scale data centers
Provides a comprehensive reference in large data center networking. It first summarizes the developing trend of DCNs, and reports four novel DCNs, including a switch-centric DCN, a modular DCN, a wireless DCN, and a hybrid DCN. Furthermore another important factor in DCN targets at managing and optimizing the network activity at the level of transfers to aggregate correlated data flows and thus directly to lower down the network traffic resulting from such data transfers. In particular, the book reports the in-network aggregation of incast transfer, shuffle transfer, uncertain incast transfer, and the cooperative scheduling of uncertain multicast transfer.
Data and Computer Communications
It is ideal for one/two-semester courses in Computer Networks, Data Communications, and Communications Networks in CS, CIS, and Electrical Engineering departments. This book is also suitable for Product Development personnel, Programmers, Systems Engineers, Network Designers and others involved in the design of data communications and networking products. With a focus on the most current technology and a convenient modular format, this best-selling text offers a clear and comprehensive survey of the entire data and computer communications field. Emphasizing both the fundamental principles as well as the critical role of performance in driving protocol and network design, it explores in detail all the critical technical areas in data communications, wide-area networking, local area networking, and protocol design.
Current trends in database technology - EDBT 2004 Workshops ; EDBT 2004 Workshops PhD, DataX, PIM, P2P&DB, and ClustWeb, Heraklion, Crete, Greece, March 14-18, 2004, Revised Selected Papers
This volume comprises papers from the following ?ve workshops that were part of the complete program for the International Conference on Extending Database Technology (EDBT) held in Heraklion, Greece, March 2004: • ICDE/EDBT Joint Ph. D. Workshop (PhD) • Database Technologies for Handling XML-information on the Web (DataX) • Pervasive Information Management (PIM) • Peer-to-Peer Computing and Databases (P2P&DB) • Clustering Information Over the Web (ClustWeb) Together, the ?ve workshops featured 61 high-quality papers selected from appr- imately 180 submissions.
Content based image retrieval systems
With an advent of technology, huge collection of digital images is formed as repositories on crime prevention, medical diagnosis, military, face finding, satellites and remote sensing. The task of searching for similar images in the repository is difficult. The data is growing enormously which makes it difficult to store and manage. The traditional image retrieval technique is inefficient in retrieving these images. Content-based image retrieval is an approach from data mining community, which provides the solution of managing this huge quantity of data. In this research, a Content-Based Image Retrieval (CBIR) system has been developed using color and texture as retrieval features from the image repository. The system allows the user to search for an image based on any of the two features alone or in combination by assigning weights to the features. The histogram and color moments approach is used to extract the color feature, texture feature is extracted using statistical moments and co-occurrence matrix method and the shape feature is extracted using the morphological operations. The images and the extracted feature vectors are stored in the Pickle file. The system is robust as it provides search based on the multiple features. The performance of the system was evaluated by analyzing the retrieval results using precision and recall.
Computing and Combinatorics ; 13th Annual International Conference, COCOON 2007, Banff, Canada, July 16-19, 2007, Proceedings
The Book covers most aspects of theoretical computer scienceand combinatorics related to computing.It exploring research, development, and novel applications of computing and combinatorics.
Computer vision systems ; 6th International conference, ICVS 2008 Santorini, Greece, May 12-15, 2008 Proceedings
This book constitutes the refereed proceedings of the 6th International Conference on Computer Vision Systems, ICVS 2008, held in Santorini, Greece, May 12-15, 2008.
Computer Vision Systems ; 2nd International Workshop, ICVS 2001 Vancouver, Canada, July 7-8, 2001 Proceedings
Computer Vision has reached a level of maturity that allows us not only to p- form research on individual methods and system components but also to build fully integrated computer vision systems of signi cant complexity. This opens a number of new problems related to system architecture, methods for system synthesis and veri cation, active vision systems, control of perception and - tion, knowledge and system representation, context modeling, cue integration, etc. By focusing on methods and concepts for the construction of fully integrated vision systems, ICVS aims to bring together researchers interested in computer vision systems. Similar to the previous event in Las Palmas, ICVS 2001 was organized as a single-track workshop consisting of high-quality.
Computer Vision Beyond the Visible Spectrum
Recently, there has been a dramatic increase in the use of sensors in the non-visible bands. As a result, there is a need for existing computer vision methods and algorithms to be adapted for use with non-visible sensors, or for the development of completely new methods and systems. Computer Vision Beyond the Visible Spectrum is the first book to bring together state-of-the-art work in this area. It presents new & pioneering research across the electromagnetic spectrum in the military, commercial, and medical domains. By providing a detailed examination of each of these areas, it focuses on the development of state-of-the-art algorithms and looks at how they can be used to solve existing & new challenges within computer vision. Essential reading for academics & industrial researchers working in the area of computer vision, image processing, and medical imaging, it will also be useful background reading for advanced undergraduate & postgraduate students.
