الصفحة 15
الصفحة 15
Deep learning pipeline : Building a deep learning model with TensorFlow
Build your own pipeline based on modern TensorFlow approaches rather than outdated engineering concepts. This book shows you how to build a deep learning pipeline for real-life TensorFlow projects. You'll learn what a pipeline is and how it works so you can build a full application easily and rapidly. Then troubleshoot and overcome basic Tensorflow obstacles to easily create functional apps and deploy well-trained models. Step-by-step and example-oriented instructions help you understand each step of the deep learning pipeline while you apply the most straightforward and effective tools to demonstrative problems and datasets.
Deep learning approach for text summarization
Machine learning and deep learning, as we know, have started ruling over almost every field in the computing industry and so, has revolutionized the process of text summarization too. Automatic text summarization is an advancing realm of the natural language processing research in which concise textual summaries are generated from lengthy input documents. Extensive research has been carried out on how automatic summarization can be prosecuted through various extractive and abstractive techniques. In this paper, we address all the approaches to text summarization and present the modus operandi of an Architecture called Encoder Decoder, under the machine learning approach.
Deep learning and computer vision in remote sensing-I
In the last few years, huge amounts of progress have been made regarding remote sensing in the field of computer vision. This success and progress is mostly due to the effectiveness of deep learning (DL) algorithms. In addition, the remote sensing community has shifted its attention to DL, and DL algorithms have been used to achieve significant success in many image analysis tasks. However, with regard to remote sensing, a number of challenges caused by difficulties in data acquisition and annotation have not been fully solved yet. This reprint is a collection of novel developments in the field of remote sensing using computer vision, deep learning, and artificial intelligence. The articles published involve fundamental theoretical analyses as well as those demonstrating their application to real-world problems.
Deep fake detection
Deep learning has been successfully applied to solve various complex problems ranging from big data analytics to computer vision and human-level control. Deep learning advances however have also been employed to create software that can cause threats to privacy, democracy and national security. One of those deep learning-powered applications recently emerged is “deepfake”. Deepfake algorithms can create fake images and videos that humans cannot distinguish them from authentic ones. The proposal of technologies that can automatically detect and assess the integrity of digital visual media is therefore indispensable.
Declarative programming for knowledge management ; 16th International conference on applications of declarative programming and knowledge management, INAP 2005, Fukuoka, Japan, October 22-24, 2005. Revised Selected Papers
Presents a selection of papers presented at the 16th Inter- tional Conference on Applications of Declarative Programming and Knowledge Management, INAP 2005,held in October 2005 at Waseda University, Fukuoka, Japan. These papers re?ect a snapshot of ongoing research and current app- cations in knowledge management and declarative programming.
Decision Procedures : An Algorithmic Point of View
Concentrates on decision procedures for first-order theories that are commonly used in automated verification and reasoning, theorem-proving, compiler optimization and operations research.
Dataset Studio
Data is the new oil, which means that AI engineers can face difficulties in locating suitable datasets. Dataset Studio is a comprehensive platform designed to support AI engineers in the creation and optimization of datasets. This project offers a diverse range of services that encompass data collection, data augmentation, and data classification. As a result, this software empowers engineers by automatically generating structured data through the utilization of advanced tools and AI techniques. By automating the laborious tasks of manual data collection and extraction, Dataset Studio effectively streamlines the workflow for AI engineers, enabling them to save valuable time and focus on the more intricate aspects of dataset development and refinement.
Data-Driven Fault Detection and Reasoning for Industrial Monitoring
Assesses the potential of data-driven methods in industrial process monitoring engineering. The process modeling, fault detection, classification, isolation, and reasoning are studied in detail. These methods can be used to improve the safety and reliability of industrial processes. Fault diagnosis, including fault detection and reasoning, has attracted engineers and scientists from various fields such as control, machinery, mathematics, and automation engineering. Combining the diagnosis algorithms and application cases, this book establishes a basic framework for this topic and implements various statistical analysis methods for process monitoring.
Database Programming Languages ; 10th international symposium, DBPL 2005, Trondheim, Norway, August 28-29, 2005, revised selected papers
Constitutes the refereed post-proceedings of the 10th International Workshop on Database Programming Languages, DBPL 2005. This book presents papers organized in topical sections on XML languages, XML and P2P data integration, XML query languages, types and XML, grammars, automata, and tree, as well as dependencies and constraints.
Database and Expert Systems Applications ; 18th International Conference, DEXA 2007, Regensburg, Germany, September 3-7, 2007, Proceedings
This volume represent the state of the art of - search in the domain of data, information and knowledge management, intelligent systems, and their applications.
Database and expert systems and Aapplications ; 17th International Conference, DEXA 2006, Krakow, Poland, September 4-8, 2006, Proceedings
The annual international conference on Database and Expert Systems Applications (DEXA) is now well established as a reference scientific event. The reader will find in this volume a collection of scientific papers that represent the state of the art of research in the domain of data, information and knowledge management, intelligent systems, and their applications.
Data Warehousing and Knowledge Discovery ; 9th International Conference, DaWaK 2007, Regensburg, Germany, September 3-7, 2007, Proceedings
Data Warehousing and Knowledge Discovery have been widely accepted as key te- nologies for enterprises and organizations to improve their abilities in data analysis, decision support, and the automatic extraction of knowledge from data. With the exponentially growing amount of information to be included in the decision-making process, the data to be processed become more and more complex in both structure and semantics. Consequently, the process of retrieval and knowledge discovery from this huge amount of heterogeneous complex data constitutes the reality check for research in the area.
Data Warehousing and Knowledge Discovery ; 4th International Conference, DaWaK 2002, Aix-en-Provence, France, September 4-6, 2002. Proceedings
Within the last few years Data Warehousing and Knowledge Discovery technology has established itself as a key technology for enterprises that wish to improve the quality of the results obtained from data analysis, decision support, and the automatic extraction of knowledge from data. The Fourth International Conference on Data Warehousing and Knowledge Discovery (DaWaK 2002) continues a series of successful conferences dedicated to this topic. Its main objective is to bring together researchers and practitioners to discuss research issues and experience in developing and deploying data warehousing and knowledge discovery systems, applications, and solutions.
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, AI, and machine learning in drug development
The confluence of big data, AI, and machine learning has led to a paradigm shift in how innovative medicines are developed and healthcare delivered. To fully capitalize on these technological advances, it is essential to systematically harness data from diverse sources and leverage digital technologies and advanced analytics to enable data-driven decisions. Data science stands at a unique moment of opportunity to lead such a transformative change. Intended to be a single source of information, Data Science, AI, and Machine Learning in Drug Research and Development covers a wide range of topics on the changing landscape of drug R&D, emerging applications of big data, AI and machine learning in drug development, and the build of robust data science organizations to drive biopharmaceutical digital transformations
Data science on the Google cloud platform : Implementing end-to-end real-time data pipelines : From ingest to machine learning
Learn how easy it is to apply sophisticated statistical and machine learning methods to real-world problems when you build using Google Cloud Platform (GCP). This hands-on guide shows data engineers and data scientists how to implement an end-to-end data pipeline with cloud native tools on GCP. You'll work through a sample business decision by employing a variety of data science approaches. Follow along by building a data pipeline in your own project on GCP, and discover how to solve data science problems in a transformative and more collaborative way. Employ best practices in building highly scalable data and ML pipelines on Google Cloud Automate and schedule data ingest using Cloud Run Create and populate a dashboard in Data Studio Build a real-time analytics pipeline using Pub/Sub, Dataflow, and BigQuery Conduct interactive data exploration with BigQuery Create a Bayesian model with Spark on Cloud Dataproc Forecast time series and do anomaly detection with BigQuery ML Aggregate within time windows with Dataflow Train explainable machine learning models with Vertex AI Operationalize ML with Vertex AI Pipelines
Data mining and machine learning applications
Elaborates in detail on the current needs of data mining and machine learning and promotes mutual understanding among research in different disciplines, thus facilitating research development and collaboration. Data, the latest currency of today’s world, is the new gold. In this new form of gold, the most beautiful jewels are data analytics and machine learning. Data mining and machine learning are considered interdisciplinary fields. Data mining is a subset of data analytics and machine learning involves the use of algorithms that automatically improve through experience based on data.
Data Integration in the Life Sciences ; Vol. 4075 ; 3rd International Workshop, DILS 2006, Hinxton, UK, July 20-22, 2006, Proceedings
Data management and data integration are fundamental problems in the life sciences. Advances in molecular biology and molecular medicine are almost u- versallyunderpinned by enormouse?orts in data management,data integration, automatic data quality assurance, and computational data analysis. Many hot topics in the life sciences, such as systems biology, personalized medicine, and pharmacogenomics, critically depend on integrating data sets and applications producedby di?erent experimentalmethods, in di?erent researchgroups,andat di?erent levels of granularity.
Data communications and network technologies
Aims to help readers master the basics of network communications and use Huawei network devices to set up enterprise LANs and WANs, wired networks, and wireless networks, ensure network security for enterprises, and grasp cutting-edge computer network technologies. The content of this book includes: network communication fundamentals, TCP/IP protocol, Huawei VRP operating system, IP addresses and subnetting, static and dynamic routing, Ethernet networking technology, ACL and AAA, network address translation, DHCP server, WLAN, IPv6, WAN PPP and PPPoE protocol, typical networking architecture and design cases of campus networks, SNMP protocol used by network management, operation and maintenance, network time protocol NTP, SND and NFV, programming, and automation.
Current Trends in Nonlinear Systems and Control : In Honor of Petar Kokotovic and Turi Nicosia
This volume is covering many topics in control theory and several different applications. The variety of their research is reflected in this book, which includes contributions from leading experts in the field ranging from mathematics to laboratory experiments.
