國立高雄大學圖資館 |

登入

回首頁

Python debugging for AI, machine learning, and cloud computinga pattern-oriented approach /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Python debugging for AI, machine learning, and cloud computingby Dmitry Vostokov.
其他題名:	a pattern-oriented approach /
作者:	Vostokov, Dmitry.
出版者:	Berkeley, CA :Apress :2024.
面頁冊數:	xxi, 233 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Machine learningComputer simulation.
電子資源:	https://doi.org/10.1007/978-1-4842-9745-2
ISBN:	9781484297452$q(electronic bk.)

Python debugging for AI, machine learning, and cloud computinga pattern-oriented approach /
Vostokov, Dmitry.

Python debugging for AI, machine learning, and cloud computinga pattern-oriented approach /[electronic resource] :by Dmitry Vostokov. - Berkeley, CA :Apress :2024. - xxi, 233 p. :ill., digital ;24 cm.

Chapter 1: Fundamental Vocabulary -- Chapter 2: Pattern-Oriented Debugging -- Chapter 3: Elementary Diagnostics Patterns -- Chapter 4: Debugging Analysis Patterns -- Chapter 5: Debugging Implementation Patterns -- Chapter 6: IDE Debugging in Cloud -- Chapter 7: Debugging Presentation Patterns -- Chapter 8: Debugging Architecture Patterns -- Chapter 9: Debugging Design Patterns -- Chapter 10: Debugging Usage Patterns -- Chapter 11: Case Study: Resource Leaks -- Chapter 12: Case Study: Deadlock -- Chapter 13: Challenges of Python Debugging in Cloud Computing -- Chapter 14: Challenges of Python Debugging in AI and Machine Learning -- Chapter 15: What AI and Machine Learning Can Do for Python Debugging -- Chapter 16: The List of Debugging Patterns.

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. You will: 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.

ISBN: 9781484297452$q(electronic bk.)

Standard No.: 10.1007/978-1-4842-9745-2doiSubjects--Topical Terms:

972660
Machine learning
--Computer simulation.

LC Class. No.: QA76.9.D43

Dewey Class. No.: 005.14

Python debugging for AI, machine learning, and cloud computinga pattern-oriented approach /
LDR:03436nmm a2200325 a 4500 001 661205
003 DE-He213
005 20231215180741.0
006 m d
007 cr nn 008maaau
008 241106s2024 cau s 0 eng d
020 $a 9781484297452$q(electronic bk.)
020 $a 9781484297445$q(paper)
024 7 $a 10.1007/978-1-4842-9745-2 $2 doi
035 $a 978-1-4842-9745-2
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.9.D43
072 7 $a UMX $2 bicssc
072 7 $a COM051360 $2 bisacsh
072 7 $a UMX $2 thema
082 0 4 $a 005.14 $2 23
090 $a QA76.9.D43 $b V971 2024
100 1 $a Vostokov, Dmitry. $3 947436
245 1 0 $a Python debugging for AI, machine learning, and cloud computing $h [electronic resource] : $b a pattern-oriented approach / $c by Dmitry Vostokov.
260 $a Berkeley, CA : $b Apress : $b Imprint: Apress, $c 2024.
300 $a xxi, 233 p. : $b ill., digital ; $c 24 cm.
505 0 $a Chapter 1: Fundamental Vocabulary -- Chapter 2: Pattern-Oriented Debugging -- Chapter 3: Elementary Diagnostics Patterns -- Chapter 4: Debugging Analysis Patterns -- Chapter 5: Debugging Implementation Patterns -- Chapter 6: IDE Debugging in Cloud -- Chapter 7: Debugging Presentation Patterns -- Chapter 8: Debugging Architecture Patterns -- Chapter 9: Debugging Design Patterns -- Chapter 10: Debugging Usage Patterns -- Chapter 11: Case Study: Resource Leaks -- Chapter 12: Case Study: Deadlock -- Chapter 13: Challenges of Python Debugging in Cloud Computing -- Chapter 14: Challenges of Python Debugging in AI and Machine Learning -- Chapter 15: What AI and Machine Learning Can Do for Python Debugging -- Chapter 16: The List of Debugging Patterns.
520 $a 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. You will: 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.
650 0 $a Machine learning $x Computer simulation. $3 972660
650 0 $a Debugging in computer science $x Computer programs. $3 954628
650 0 $a Python (Computer program language) $3 215247
650 1 4 $a Python. $3 763308
650 2 4 $a Artificial Intelligence. $3 212515
650 2 4 $a Machine Learning. $3 833608
650 2 4 $a Cloud Computing. $3 777671
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-1-4842-9745-2
950 $a Professional and Applied Computing (SpringerNature-12059)