Machine learning approach cloud (27 Ergebnisse)

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Taschenbuch. Zustand: Neu. Python Debugging for AI, Machine Learning, and Cloud Computing | A Pattern-Oriented Approach | Dmitry Vostokov | Taschenbuch | xxi | Englisch | 2023 | Apress | EAN 9781484297445 | Verantwortliche Person für die EU: APress in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.…

Zustand: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | This book is for those who wish to understand how Python debugging is and can be used to develop robust and reliable AI, machine learning, and cloud computing software. It will teach you a novel pattern-oriented approach to diagnose and debug abnormal software structure and behavior. The book begins with an introduction to the pattern-oriented software diagnostics and debugging process that, before performing Python debugging, diagnoses problems in various software artifacts such as memory dumps, traces, and logs. Next, yoüll learn to use various debugging patterns through Python case studies that model abnormal software behavior. Yoüll also be exposed to Python debugging techniques specific to cloud native and machine learning environments and explore how recent advances in AI/ML can help in Python debugging. Over the course of the book, case studies will show you how to resolve issues around environmental problems, crashes, hangs, resource spikes, leaks, and performancedegradation. This includes tracing, logging, and analyzing memory dumps using native WinDbg and GDB debuggers. Upon completing this book, you will have the knowledge and tools needed to employ Python debugging in the development of AI, machine learning, and cloud computing applications. What You Will Learn Employ a pattern-oriented approach to Python debugging that starts with diagnostics of common software problems Use tips and tricks to get the most out of popular IDEs, notebooks, and command-line Python debugging Understand Python internals for interfacing with operating systems and external modules Perform Python memory dump analysis, tracing, and logging Who This Book Is For Software developers, AI/ML engineers, researchers, data engineers, as well as MLOps and DevOps professionals.…

Zustand: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | This book is for those who wish to understand how Python debugging is and can be used to develop robust and reliable AI, machine learning, and cloud computing software. It will teach you a novel pattern-oriented approach to diagnose and debug abnormal software structure and behavior. The book begins with an introduction to the pattern-oriented software diagnostics and debugging process that, before performing Python debugging, diagnoses problems in various software artifacts such as memory dumps, traces, and logs. Next, yoüll learn to use various debugging patterns through Python case studies that model abnormal software behavior. Yoüll also be exposed to Python debugging techniques specific to cloud native and machine learning environments and explore how recent advances in AI/ML can help in Python debugging. Over the course of the book, case studies will show you how to resolve issues around environmental problems, crashes, hangs, resource spikes, leaks, and performancedegradation. This includes tracing, logging, and analyzing memory dumps using native WinDbg and GDB debuggers. Upon completing this book, you will have the knowledge and tools needed to employ Python debugging in the development of AI, machine learning, and cloud computing applications. What You Will Learn Employ a pattern-oriented approach to Python debugging that starts with diagnostics of common software problems Use tips and tricks to get the most out of popular IDEs, notebooks, and command-line Python debugging Understand Python internals for interfacing with operating systems and external modules Perform Python memory dump analysis, tracing, and logging Who This Book Is For Software developers, AI/ML engineers, researchers, data engineers, as well as MLOps and DevOps professionals.…

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Gebunden. Zustand: New. AudienceResearchers and industry engineers in computer science and artificial intelligence, IT professionals, network administrators, cybersecurity experts.Sachi Nandan Mohanty received his PhD from IIT Kharagpur 2015 and he is now an associate professor in.

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Buch. Zustand: Neu. Neuware - Machine Learning Approach for Cloud Data Analytics in IoT The book covers the multidimensional perspective of machine learning through the perspective of cloud computing and Internet of Things ranging from fundamentals to advanced applications Sustainable computing paradigms like cloud and fog are capable of handling issues related to performance, storage and processing, maintenance, security, efficiency, integration, cost, energy and latency in an expeditious manner. In order to expedite decision-making involved in the complex computation and processing of collected data, IoT devices are connected to the cloud or fog environment. Since machine learning as a service provides the best support in business intelligence, organizations have been making significant investments in this technology. Machine Learning Approach for Cloud Data Analytics in IoT elucidates some of the best practices and their respective outcomes in cloud and fog computing environments. It focuses on all the various research issues related to big data storage and analysis, large-scale data processing, knowledge discovery and knowledge management, computational intelligence, data security and privacy, data representation and visualization, and data analytics. The featured technologies presented in the book optimizes various industry processes using business intelligence in engineering and technology. Light is also shed on cloud-based embedded software development practices to integrate complex machines so as to increase productivity and reduce operational costs. The various practices of data science and analytics which are used in all sectors to understand big data and analyze massive data patterns are also detailed in the book.; Im Zeitalter des Internet of Things (IoT) erzeugen Edge-Geräte in jedem Sekundenbruchteil gigantische Datenmengen. Dabei besteht das Hauptziel dieser Netzwerke darin, aus den gesammelten Daten sinnvolle Informationen abzuleiten. Gleichzeitig werden gewaltige Datenmengen in die Cloud übertragen, was extrem teuer und zeitaufwändig ist. Es ist somit notwendig, effiziente Mechanismen für die Verarbeitung dieser gewaltigen Datenmengen zu entwickeln, und dafür sind effiziente Datenverarbeitungstechniken erforderlich. Nachhaltige Paradigmen wie Cloud Computing und Fog Computing tragen zu einem geschickten Umgang mit Themen wie Leistung, Speicher- und Verarbeitungskapazitäten, Wartung, Sicherheit, Effizienz, Integration, Kosten, Energieverbrauch und Latenzzeiten bei. Allerdings werden ausgefeilte Analysetools benötigt, um die Anfragen in einer optimalen Zeit zu bearbeiten. Daher wird derzeit eifrig an der Entwicklung eines effektiven und effizienten Rahmens geforscht, um den größtmöglichen Nutzen zu erhalten. Bei der Verarbeitung der gewaltigen Datenmengen steht das maschinelle Lernen besonders hoch im Kurs und wird in zahlreichen Disziplinen angewandt, auch in den sozialen Medien. In Machine Learning Approach for Cloud Data Analytics in IoT werden sämtliche Aspekte des IoT, des Cloud Computing und der Datenanalyse ausführlich erläutert und aus verschiedenen Perspektiven betrachtet. Das Buch präsentiert den neuesten Stand der Forschung und fortschrittliche Themen. So erhalten die Leserinnen und Leser aktuelle Informationen und können das gesamte Spektrum der Anwendungen von IoT, Cloud Computing und Datenanalyse erfassen.…

Zustand: New. 2021. 1st Edition. Hardcover. . . . . . Books ship from the US and Ireland.