Machine learning engineering with Python: manage the lifecycle of machine learning models using MLOps with practical examples
The Second Edition of Machine Learning Engineering with Python is the practical guide that MLOps and ML engineers need to build solutions to real-world problems. It will provide you with the skills you need to stay ahead in this rapidly evolving field. The book takes an examples-based approach to he...
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| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Birmingham, UK
Packt Publishing Ltd.
2023
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| Ausgabe: | Second edition. |
| Schriftenreihe: | Expert insight
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| Schlagwörter: | |
| Links: | https://learning.oreilly.com/library/view/-/9781837631964/?ar |
| Zusammenfassung: | The Second Edition of Machine Learning Engineering with Python is the practical guide that MLOps and ML engineers need to build solutions to real-world problems. It will provide you with the skills you need to stay ahead in this rapidly evolving field. The book takes an examples-based approach to help you develop your skills and covers the technical concepts, implementation patterns, and development methodologies you need. You'll explore the key steps of the ML development lifecycle and create your own standardized "model factory" for training and retraining of models. You'll learn to employ concepts like CI/CD and how to detect different types of drift. Get hands-on with the latest in deployment architectures and discover methods for scaling up your solutions. This edition goes deeper in all aspects of ML engineering and MLOps, with emphasis on the latest open-source and cloud-based technologies. This includes a completely revamped approach to advanced pipelining and orchestration techniques. With a new chapter on deep learning, generative AI, and LLMOps, you will learn to use tools like LangChain, PyTorch, and Hugging Face to leverage LLMs for supercharged analysis. You will explore AI assistants like GitHub Copilot to become more productive, then dive deep into the engineering considerations of working with deep learning. |
| Beschreibung: | Includes index |
| Umfang: | 1 Online-Ressource (462 Seiten) illustrations. |
| ISBN: | 9781837634354 1837634351 9781837631964 |
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| id | ZDB-30-ORH-096663952 |
| illustrated | Illustrated |
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| isbn | 9781837634354 1837634351 9781837631964 |
| language | English |
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| physical | 1 Online-Ressource (462 Seiten) illustrations. |
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| series2 | Expert insight |
| spelling | McMahon, Andrew P. VerfasserIn aut Machine learning engineering with Python manage the lifecycle of machine learning models using MLOps with practical examples Andrew P. McMahon ; foreword by Adi Polak Second edition. Birmingham, UK Packt Publishing Ltd. 2023 1 Online-Ressource (462 Seiten) illustrations. Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Expert insight Includes index The Second Edition of Machine Learning Engineering with Python is the practical guide that MLOps and ML engineers need to build solutions to real-world problems. It will provide you with the skills you need to stay ahead in this rapidly evolving field. The book takes an examples-based approach to help you develop your skills and covers the technical concepts, implementation patterns, and development methodologies you need. You'll explore the key steps of the ML development lifecycle and create your own standardized "model factory" for training and retraining of models. You'll learn to employ concepts like CI/CD and how to detect different types of drift. Get hands-on with the latest in deployment architectures and discover methods for scaling up your solutions. This edition goes deeper in all aspects of ML engineering and MLOps, with emphasis on the latest open-source and cloud-based technologies. This includes a completely revamped approach to advanced pipelining and orchestration techniques. With a new chapter on deep learning, generative AI, and LLMOps, you will learn to use tools like LangChain, PyTorch, and Hugging Face to leverage LLMs for supercharged analysis. You will explore AI assistants like GitHub Copilot to become more productive, then dive deep into the engineering considerations of working with deep learning. Machine learning Python (Computer program language) Data mining Apprentissage automatique Python (Langage de programmation) Exploration de données (Informatique) Polak, Adi MitwirkendeR ctb |
| spellingShingle | McMahon, Andrew P. Machine learning engineering with Python manage the lifecycle of machine learning models using MLOps with practical examples Machine learning Python (Computer program language) Data mining Apprentissage automatique Python (Langage de programmation) Exploration de données (Informatique) |
| title | Machine learning engineering with Python manage the lifecycle of machine learning models using MLOps with practical examples |
| title_auth | Machine learning engineering with Python manage the lifecycle of machine learning models using MLOps with practical examples |
| title_exact_search | Machine learning engineering with Python manage the lifecycle of machine learning models using MLOps with practical examples |
| title_full | Machine learning engineering with Python manage the lifecycle of machine learning models using MLOps with practical examples Andrew P. McMahon ; foreword by Adi Polak |
| title_fullStr | Machine learning engineering with Python manage the lifecycle of machine learning models using MLOps with practical examples Andrew P. McMahon ; foreword by Adi Polak |
| title_full_unstemmed | Machine learning engineering with Python manage the lifecycle of machine learning models using MLOps with practical examples Andrew P. McMahon ; foreword by Adi Polak |
| title_short | Machine learning engineering with Python |
| title_sort | machine learning engineering with python manage the lifecycle of machine learning models using mlops with practical examples |
| title_sub | manage the lifecycle of machine learning models using MLOps with practical examples |
| topic | Machine learning Python (Computer program language) Data mining Apprentissage automatique Python (Langage de programmation) Exploration de données (Informatique) |
| topic_facet | Machine learning Python (Computer program language) Data mining Apprentissage automatique Python (Langage de programmation) Exploration de données (Informatique) |
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