Python Debugging for AI, Machine Learning, and Cloud Computing pdf
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Python Debugging for AI, Machine Learning, and Cloud Computing

Dmitry Vostokov


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Dmitriy Vostokov's book, "Python Debugging for AI, Machine Learning, and Cloud Computing," is an essential desktop reference for developers working in the fields of artificial intelligence, machine learning, and cloud computing. This edition offers an in-depth exploration into debugging methods specific to complex computing environments and large data volumes.

This publication is considered an indispensable resource for anyone looking to deepen their knowledge and skills in debugging complex systems. By mastering the techniques presented, you will significantly enhance the quality and reliability of your software solutions. Don't miss your chance to become a master of debugging—download the book "Python Debugging for AI, Machine Learning, and Cloud Computing" PDF today.

What’s inside the book?

The guide discusses Python code debugging methods used in developing AI and ML models, as well as applications in cloud infrastructure. It starts with the basics of debugging, gradually moving to more complex topics, including resource management, application state monitoring, and performance optimization.

You will learn how to identify and fix complex errors in code, which is particularly relevant when working with big data and in distributed systems. Each chapter is accompanied by practical examples and best practices.

The Absolute Python Debugging for AI, Machine Learning, and Cloud Computing pdf

Who is this guide suitable for?

  1. Beginners in programming. Helps master debugging skills at an introductory level.
  2. Professional AI and ML developers. Offers advanced debugging methods for specific tasks.
  3. Cloud technology specialists. Discusses debugging of distributed applications.
  4. Researchers. Assists in optimizing experimental code.

What are the pros and cons of this book?

Pros:

  • Extensive coverage of the debugging topic in key technological areas.
  • Practical examples that can be directly applied in work.
  • Tips for using modern tools and libraries for debugging.

Cons:

  • High entry barrier for readers without basic Python knowledge.
  • May seem too technical and overloaded with information for beginners.

More About the Author of the Book

Dmitry Vostokov

He is a globally renowned expert in the fields of software diagnostics, forensics, and prognostics, having founded the discipline of pattern-oriented software diagnostics. His extensive expertise is encapsulated in the Software Diagnostics Institute (DA+TA: DumpAnalysis.org + TraceAnalysis.org).

With a professional background spanning over thirty years, Dmitry has amassed substantial experience in software architecture, design, development, and maintenance across various industries.

FAQ for "Python Debugging for AI, Machine Learning, and Cloud Computing"

Question 1: What debugging tools are recommended in the book?

It covers the use of PDB, PyCharm, and specialized libraries like TensorFlow Debugger.

Question 2: Will the textbook be useful for debugging non-AI systems?

Absolutely, the methods and approaches can be applied in any Python project.

Question 3: Does the guide contain materials on dealing with errors in real-time?

Yes, it includes chapters dedicated to reactive debugging and real-time application monitoring.

Question 4: How does the book help improve the performance of AI models?

It offers methods for optimizing code and eliminating bottlenecks that may slow down data processing.

Question 5: Are there sections dedicated to automating debugging processes?

The guide includes an overview of tools and scripts for automating testing and debugging.

Information

Author: Dmitry Vostokov Language: English
Publisher: Apress ISBN-13: 978-1484297445
Publication Date: December 16, 2023 ISBN-10: 148429744X
Print Length: 256 pages


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