This is a practical guide to building ML solutions to real-world problems. Andrew P. McMahon takes an examples-based approach and covers technical concepts, implementation patterns, and development methodologies. This edition has a new chapter on deep learning, generative AI, and LLMOps, and covers tools like LangChain, PyTorch, and Hugging Face to use LLMs for analysis. The book also looks at AI assistants like GitHub Copilot.

<ASIN:1837631964>

Author: Andrew P. McMahon
Publisher: Packt Publishing
Date: August 2023
Pages: 462
ISBN: 9781837631964
Print:1837631964
Kindle:B0BXXQJC2D
Audience: Python developers interested in machine learning
Level: Intermediate
Category: Artificial Intelligence

Topics covered:

• Plan and manage end-to-end ML development projects
• Explore deep learning, LLMs, and LLMOps to leverage generative AI
• Use Python to package your ML tools and scale up your solutions
• Get to grips with Apache Spark, Kubernetes, and Ray
• Build and run ML pipelines with Apache Airflow, ZenML, and Kubeflow
• Detect drift and build retraining mechanisms into your solutions
• Improve error handling with control flows and vulnerability scanning
• Host and build ML microservices and batch processes running on AWS

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