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Machine Learning Infrastructure and Best Practices for Software Engineers

You're reading from   Machine Learning Infrastructure and Best Practices for Software Engineers Take your machine learning software from a prototype to a fully fledged software system

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Product type Paperback
Published in Jan 2024
Publisher Packt
ISBN-13 9781837634064
Length 346 pages
Edition 1st Edition
Languages
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Author (1):
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Miroslaw Staron Miroslaw Staron
Author Profile Icon Miroslaw Staron
Miroslaw Staron
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Table of Contents (24) Chapters Close

Preface 1. Part 1:Machine Learning Landscape in Software Engineering
2. Machine Learning Compared to Traditional Software FREE CHAPTER 3. Elements of a Machine Learning System 4. Data in Software Systems – Text, Images, Code, and Their Annotations 5. Data Acquisition, Data Quality, and Noise 6. Quantifying and Improving Data Properties 7. Part 2: Data Acquisition and Management
8. Processing Data in Machine Learning Systems 9. Feature Engineering for Numerical and Image Data 10. Feature Engineering for Natural Language Data 11. Part 3: Design and Development of ML Systems
12. Types of Machine Learning Systems – Feature-Based and Raw Data-Based (Deep Learning) 13. Training and Evaluating Classical Machine Learning Systems and Neural Networks 14. Training and Evaluation of Advanced ML Algorithms – GPT and Autoencoders 15. Designing Machine Learning Pipelines (MLOps) and Their Testing 16. Designing and Implementing Large-Scale, Robust ML Software 17. Part 4: Ethical Aspects of Data Management and ML System Development
18. Ethics in Data Acquisition and Management 19. Ethics in Machine Learning Systems 20. Integrating ML Systems in Ecosystems 21. Summary and Where to Go Next 22. Index 23. Other Books You May Enjoy

To know where we’re going, we need to know where 
we’ve been

My journey with computers started in the early 1990s, with Atari 800XL. Once I got my hands on that computer, I was amazed by the sheer fact that it could do what I told it to do. My first program was, of course, a program in BASIC:

10 PRINT Hello world!
20 GOTO 10

It’s neither well-formed nor a very useful program, but that was all I could do at the time. This first program shaped my entire career as it sparked my interest in software development. Later on, during my professional career, I realized that professional software engineering is much more than just writing source code and compiling it. The programs need to be well-formed, well-documented, well-designed, and well-tested (among many other things). This observation, in turn, shaped my view on software engineering as a discipline that can turn homebrewed software into a piece of art that can be used over long periods if well maintained...

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