python debugging machine learning di vostokov dmitry (23 risultati)

Condizione: Hervorragend. Zustand: Hervorragend | Seiten: 240 | Sprache: Englisch | Produktart: Bücher.

Condizione: Sehr gut. Zustand: Sehr gut | Seiten: 240 | Sprache: Englisch | Produktart: Bücher.

paperback. Condizione: Fine.

Paperback or Softback. Condizione: New. Python Debugging for Ai, Machine Learning, and Cloud Computing: A Pattern-Oriented Approach 0.99. Book.

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Condizione: New.

Condizione: New. Brand New. Soft Cover International Edition. Different ISBN and Cover Image. Priced lower than the standard editions which is usually intended to make them more affordable for students abroad. The core content of the book is generally the same as the standard edition. The country selling restrictions may be printed on the book but is no problem for the self-use. This Item maybe shipped from US or any other country as we have multiple locations worldwide.

Condizione: Brand New. New.SoftCover International edition. Different ISBN and Cover image but contents are same as US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

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

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Paperback. Condizione: Brand New. 254 pages. 10.00x7.01x0.54 inches. In Stock.

Paperback / softback. Condizione: New. New copy - Usually dispatched within 4 working days. 493.

Taschenbuch. Condizione: Neu. Neuware -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 LearnEmploy a pattern-oriented approach to Python debugging that starts with diagnostics of common software problemsUse tips and tricks to get the most out of popular IDEs, not Elektronisches Buch, and command-line Python debuggingUnderstand Python internals for interfacing with operating systems and external modulesPerform Python memory dump analysis, tracing, and loggingWho This Book Is ForSoftware developers, AI/ML engineers, researchers, data engineers, as well as MLOps and DevOps professionals.APress in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin 256 pp. Englisch.

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Paperback / softback. Condizione: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 493.

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Covers diagnostics in AI/ML and cloud environments, such as crashes, hangs, CPU, and memory consumptionTeaches Python code interaction with Windows and Linux necessary for effective diagnostics and debuggingExplains pattern-oriented approac.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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, you'll learn to use various debugging patterns through Python case studies that model abnormal software behavior. You'll 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 performance degradation. This includes tracing, logging, and analyziing 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 LearnEmploy a pattern-oriented approach to Python debugging that starts with diagnostics of common software problemsUse tips and tricks to get the most out of popular IDEs, not Elektronisches Buch, and command-line Python debuggingUnderstand Python internals for interfacing with operating systems and external modulesPerform Python memory dump analysis, tracing, and loggingWho This Book Is ForSoftware developers, AI/ML engineers, researchers, data engineers, as well as MLOps and DevOps professionals. 256 pp. Englisch.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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, you'll learn to use various debugging patterns through Python case studies that model abnormal software behavior. You'll 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 LearnEmploy a pattern-oriented approach to Python debugging that starts with diagnostics of common software problemsUse tips and tricks to get the most out of popular IDEs, not Elektronisches Buch, and command-line Python debuggingUnderstand Python internals for interfacing with operating systems and external modulesPerform Python memory dump analysis, tracing, and loggingWho This Book Is ForSoftware developers, AI/ML engineers, researchers, data engineers, as well as MLOps and DevOps professionals.