masoud rizk (26 risultati)

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Paperback. Condizione: New. Tackle the core challenges related to enterprise-ready graph representation and learning. With this hands-on guide, applied data scientists, machine learning engineers, and practitioners will learn how to build an E2E graph learning pipeline. You'll explore core challenges at each pipeline stage, from data acquisition and representation to real-time inference and feedback loop retraining.Drawing on their experience building scalable and production-ready graph learning pipelines, the authors take you through the process of building the E2E graph learning pipeline in a world of dynamic and evolving graphs.Understand the importance of graph learning for boosting enterprise-grade applicationsNavigate the challenges surrounding the development and deployment of enterprise-ready graph learning and inference pipelinesUse traditional and advanced graph learning techniques to tackle graph use casesUse and contribute to PyGraf, an open source graph learning library, to help embed best practices while building graph applicationsDesign and implement a graph learning algorithm using publicly available and syntactic dataApply privacy-preserved techniques to the graph learning process.

Condizione: New.

Condizione: New. In.

Paperback. Condizione: New. Tackle the core challenges related to enterprise-ready graph representation and learning. With this hands-on guide, applied data scientists, machine learning engineers, and practitioners will learn how to build an E2E graph learning pipeline. You'll explore core challenges at each pipeline stage, from data acquisition and representation to real-time inference and feedback loop retraining.Drawing on their experience building scalable and production-ready graph learning pipelines, the authors take you through the process of building the E2E graph learning pipeline in a world of dynamic and evolving graphs.Understand the importance of graph learning for boosting enterprise-grade applicationsNavigate the challenges surrounding the development and deployment of enterprise-ready graph learning and inference pipelinesUse traditional and advanced graph learning techniques to tackle graph use casesUse and contribute to PyGraf, an open source graph learning library, to help embed best practices while building graph applicationsDesign and implement a graph learning algorithm using publicly available and syntactic dataApply privacy-preserved techniques to the graph learning process.

paperback. Condizione: New.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: New. 1st edition NO-PA16APR2015-KAP.

Condizione: New.

Paperback. Condizione: Brand New. 400 pages. 9.19x7.00x9.19 inches. In Stock.

Paperback. Condizione: New. Tackle the core challenges related to enterprise-ready graph representation and learning. With this hands-on guide, applied data scientists, machine learning engineers, and practitioners will learn how to build an E2E graph learning pipeline. You'll explore core challenges at each pipeline stage, from data acquisition and representation to real-time inference and feedback loop retraining.Drawing on their experience building scalable and production-ready graph learning pipelines, the authors take you through the process of building the E2E graph learning pipeline in a world of dynamic and evolving graphs.Understand the importance of graph learning for boosting enterprise-grade applicationsNavigate the challenges surrounding the development and deployment of enterprise-ready graph learning and inference pipelinesUse traditional and advanced graph learning techniques to tackle graph use casesUse and contribute to PyGraf, an open source graph learning library, to help embed best practices while building graph applicationsDesign and implement a graph learning algorithm using publicly available and syntactic dataApply privacy-preserved techniques to the graph learning process.

Condizione: New.

Taschenbuch. Condizione: Neu. On Multi-Objective Optimization Based on Hybrid Intelligent System | Hybridizing the Firefly Algorithm and the Ant Colony Algorithm to Solve Optimization Problems | Rizk Masoud Rizk-Allah | Taschenbuch | 180 S. | Englisch | 2014 | LAP LAMBERT Academic Publishing | EAN 9783659551826 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.

Paperback. Condizione: New. Tackle the core challenges related to enterprise-ready graph representation and learning. With this hands-on guide, applied data scientists, machine learning engineers, and practitioners will learn how to build an E2E graph learning pipeline. You'll explore core challenges at each pipeline stage, from data acquisition and representation to real-time inference and feedback loop retraining.Drawing on their experience building scalable and production-ready graph learning pipelines, the authors take you through the process of building the E2E graph learning pipeline in a world of dynamic and evolving graphs.Understand the importance of graph learning for boosting enterprise-grade applicationsNavigate the challenges surrounding the development and deployment of enterprise-ready graph learning and inference pipelinesUse traditional and advanced graph learning techniques to tackle graph use casesUse and contribute to PyGraf, an open source graph learning library, to help embed best practices while building graph applicationsDesign and implement a graph learning algorithm using publicly available and syntactic dataApply privacy-preserved techniques to the graph learning process.

Paperback. Condizione: Brand New. 400 pages. 9.19x7.00x9.19 inches. In Stock. This item is printed on demand.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book introduced a hybrid optimization algorithm that integrates the merits of the ant colony optimization (ACO) and firefly algorithm (FA) that used to solve optimization problems. The methodology of the book is mainly focused on the original principle behind each of the two algorithms and their applications are discussed. Also we introduced new trend for hybridizing the ant colony optimization and the firefly algorithm to solve unconstrained optimization problems, constrained optimization problems and multi-objective optimization problems. 180 pp. Englisch.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Ant Colony Optimization (ACO) is a meta-heuristic algorithm which has been successfully applied to tackle various combinatorial optimization problems, but its ability to cope with multi-objective optimization problems is yet to be explored widely. Since most real-world search and optimization problems are naturally posed as non-linear programming problems having multi-objective problems. Therefore, the principal goal of this work aims to implement a specialized version of the ant colony optimization algorithm capable of finding a set of solutions for multi-objective optimization problems. Features relevant to ant colony optimization include a highly efficient form of best-path exploitation (pheromone detection), and a sensible mechanism for exploration (probabilistic path selection). The results demonstrate superiority of the proposed algorithm and confirm its potential to solve the multi-objective problems and engineering applications. 176 pp. Englisch.

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Masoud Rizk Allah RizkRizk M. Rizk Allah obtained his Ph.D in Engineering Mathematics from Faculty of Engineering ,Menoufia University, Egypt. He has been with the Basic Engineering Sciences Department, Faculty of Engineering ,Menouf.

Taschenbuch. Condizione: Neu. On Multi-objective Optimization Based on Ant Colony Optimization | Developing an Ant Colony Optimization Algorithm for Engineering Applications | Rizk Masoud Rizk Allah (u. a.) | Taschenbuch | 176 S. | Englisch | 2014 | LAP LAMBERT Academic Publishing | EAN 9783659553226 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu Print on Demand.

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Ant Colony Optimization (ACO) is a meta-heuristic algorithm which has been successfully applied to tackle various combinatorial optimization problems, but its ability to cope with multi-objective optimization problems is yet to be explored widely. Since most real-world search and optimization problems are naturally posed as non-linear programming problems having multi-objective problems. Therefore, the principal goal of this work aims to implement a specialized version of the ant colony optimization algorithm capable of finding a set of solutions for multi-objective optimization problems. Features relevant to ant colony optimization include a highly efficient form of best-path exploitation (pheromone detection), and a sensible mechanism for exploration (probabilistic path selection). The results demonstrate superiority of the proposed algorithm and confirm its potential to solve the multi-objective problems and engineering applications.Books on Demand GmbH, Überseering 33, 22297 Hamburg 176 pp. Englisch.

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book introduced a hybrid optimization algorithm that integrates the merits of the ant colony optimization (ACO) and firefly algorithm (FA) that used to solve optimization problems. The methodology of the book is mainly focused on the original principle behind each of the two algorithms and their applications are discussed. Also we introduced new trend for hybridizing the ant colony optimization and the firefly algorithm to solve unconstrained optimization problems, constrained optimization problems and multi-objective optimization problems.Books on Demand GmbH, Überseering 33, 22297 Hamburg 180 pp. Englisch.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book introduced a hybrid optimization algorithm that integrates the merits of the ant colony optimization (ACO) and firefly algorithm (FA) that used to solve optimization problems. The methodology of the book is mainly focused on the original principle behind each of the two algorithms and their applications are discussed. Also we introduced new trend for hybridizing the ant colony optimization and the firefly algorithm to solve unconstrained optimization problems, constrained optimization problems and multi-objective optimization problems.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Ant Colony Optimization (ACO) is a meta-heuristic algorithm which has been successfully applied to tackle various combinatorial optimization problems, but its ability to cope with multi-objective optimization problems is yet to be explored widely. Since most real-world search and optimization problems are naturally posed as non-linear programming problems having multi-objective problems. Therefore, the principal goal of this work aims to implement a specialized version of the ant colony optimization algorithm capable of finding a set of solutions for multi-objective optimization problems. Features relevant to ant colony optimization include a highly efficient form of best-path exploitation (pheromone detection), and a sensible mechanism for exploration (probabilistic path selection). The results demonstrate superiority of the proposed algorithm and confirm its potential to solve the multi-objective problems and engineering applications.