الصفحة 9
الصفحة 9
Advances in information systems ; 3rd International Conference, ADVIS 2004, Izmir, Turkey, October 20-22, 2004. Proceedings
This volume contains the proceedings of the 3rd International Conference on AdvancesinInformationSystems (ADVIS)heldinIzmir,Turkey, 2004. The conference covered many of the topics of the second one: databases and data warehouses, information systems development and management, - formation retrieval, distributed and parallel data processing, and evolutionary algorithms. Besides them some of the hot topics related to information systems were included in the scope of this conference, such as data mining and kno- edge discovery, Web information systems development, information privacy and security, multimedia information systems, and network management.
Advances in Enterprise Engineering I ; 4th International Workshop CIAO! and 4th International Workshop EOMAS, held at CAiSE 2008, Montpellier, France, June 16-17, 2008. Proceedings
This book constitutes the proceedings of the 4th International Workshop on Cooperation and Interoperability, Architecture and Ontology, CIAO!, and the 4th International Workshop on Enterprise and Organizational Modeling and Simulation, EOMAS, held at CAiSE 2008 in Montpellier, France, in June 2008.
Advances in Case-Based Reasoning ; 9th European Conference, ECCBR 2008 , Trier, Germany, September 1-4, 2008. Proceedings
Constitutes the refereed proceedings of the 9th European Conference on Case-Based Reasoning, ECCBR 2008, held in Trier, Germany, in September 2008.
Advanced Trends in ICT for Innovative Business Management
Contains a collection of scientific chapters addressing the emerging trends in IT and telecommunications, as well as the issues that accompany them in business. It addresses issues in cyber applications, ICT solutions and innovative cyber know-how, and demonstrates how high-tech IT communications resources can be used to improve business production, sales and service strategies, supply chains and logistics.
Advanced machine learning and deep learning approaches for remote sensing
Provides research on how technologies such as artificial intelligence-based machine learning and deep learning can be applied to remote sensing. Through this, we can see the process of solving the existing problems of image and image signal processing for remote sensing. These techniques are computationally intensive and require the help of high-performance computing devices. With the development of devices such as GPUs, remote sensing technology, and aerial sensing technology, it is possible to monitor the Earth with high-resolution images and to obtain vast amounts of Earth observation data. The papers published in this reprint describe recent advances in big data processing and artificial intelligence-based technologies for remote sensing technology.
Advanced Data Mining and Applications ; 4th International Conference, ADMA 2008, Chengdu, China, October 8-10, 2008. Proceedings
This book constitutes the refereed proceedings of the 4th International Conference on Advanced Data Mining and Applications, ADMA 2008, held in Chengdu, China, in October 2008.
Adaptive Machine Learning Algorithms with Python : Solve Data Analytics and Machine Learing Problems on Edge Devices
Learn to use adaptive algorithms to solve real-world streaming data problems. This book covers a multitude of data processing challenges, ranging from the simple to the complex. At each step, you will gain insight into real-world use cases, find solutions, explore code used to solve these problems, and create new algorithms for your own use. You will: Apply adaptive algorithms to practical applications and examples / Understand the relevant data representation features and computational models for time-varying multi-dimensional data / Derive adaptive algorithms for mean, median, covariance, eigenvectors (PCA) and generalized eigenvectors with experiments on real data / Speed up your algorithms and put them to use on real-world stationary and non-stationary data / Master the applications of adaptive algorithms on critical edge device computation applications
A General introduction to data analytics
A guide to the principles and methods of data analysis that does not require knowledge of statistics or programming. A guide to the reasoning behind data mining techniques. A unique illustrative example that extends throughout all the chapters. Exercises at the end of each chapter and larger projects at the end of each of the text’s two main parts
