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Machine Learning Engineering with Python. Manage the lifecycle of machine learning models using MLOps with practical examples - Second Edition - Helion

Machine Learning Engineering with Python. Manage the lifecycle of machine learning models using MLOps with practical examples - Second Edition
ebook
Autor: Andrew P. McMahon, Adi Polak
Tytuł oryginału: Machine Learning Engineering with Python. Manage the lifecycle of machine learning models using MLOps with practical examples - Second Edition
ISBN: 9781837634354
stron: 462, Format: ebook
Data wydania: 2023-08-31
Księgarnia: Helion

Cena książki: 125,10 zł (poprzednio: 139,00 zł)
Oszczędzasz: 10% (-13,90 zł)

Dodaj do koszyka Machine Learning Engineering with Python. Manage the lifecycle of machine learning models using MLOps with practical examples - Second Edition

Osoby, które kupiÅ‚y tÄ™ książkÄ™, wybieraÅ‚y także »

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.

Dodaj do koszyka Machine Learning Engineering with Python. Manage the lifecycle of machine learning models using MLOps with practical examples - Second Edition

 

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Dodaj do koszyka Machine Learning Engineering with Python. Manage the lifecycle of machine learning models using MLOps with practical examples - Second Edition

Spis treści

Machine Learning Engineering with Python. Manage the lifecycle of machine learning models using MLOps with practical examples - Second Edition eBook -- spis treści

  • 1. Introduction to ML Engineering
  • 2. The Machine Learning Development Process
  • 3. From Model to Model Factory
  • 4. Packaging Up
  • 5. Deployment Patterns and Tools
  • 6. Scaling Up
  • 7. Deep Learning, Generative AI, and LLMOps
  • 8. Building an Example ML Microservice
  • 9. Building an Extract, Transform, Machine Learning Use Case

Dodaj do koszyka Machine Learning Engineering with Python. Manage the lifecycle of machine learning models using MLOps with practical examples - Second Edition

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