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Books in the "AI Mastery" Series… Enterprise AI Playbook — Business Transformation Strategies for Every Industry: https://
link.amazon/B0d7xDjsA The Complete Generative AI Engineer Cookbook for Everyone: Become a GenAI Specialist with Python: https://
link.amazon/B0bOR8Oob and more:
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Upcoming release from @ManningBooks — you can preorder this book now with the *very beneficial* Amazon price guarantee. "LLM Customization and Fine-Tuning: Adaptation, distillation, and alignment" Check it out: https://
amzn.to/46MJ6g3 Publisher's comment: "For ML engineers,
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New release from @PacktPublishing @PacktDataML Building Production AI Agents for the Web — Design and orchestrate autonomous agents with MCP, Multi-Agent Patterns, and Harness Engineering: https://
link.amazon/B07MODeKJ What you will learn:
• Integrate LLMs into web apps and extend
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Vector Search for Practitioners with Elastic — A toolkit for building NLProc solutions for search, observability, and security: https://
amzn.to/3vEkWFe v/ @PacktDataML What you will learn:
🟠Optimize performance by harnessing the capabilities of vector search
🟠Explore image
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“Generative AI with Python: The Developer’s Guide to Pretrained LLMs, Vector Databases, Retrieval Augmented Generation, and Agentic Systems”
[392 pages] Available at https://
amzn.to/4sa1MiY
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Python Machine Learning By Example: https://
amzn.to/3MczBwk v/ @PacktDataML [4th Edition]
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GitHub: https://
github.com/PacktPublishin… 518-pages! What you will learn: 🟣Machine learning best practices throughout data preparation and model development 🟣Build and improve image
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💥Scikit-learn Cookbook — 80+ recipes for Machine Learning in Python with scikit-learn [3rd Edition]: https://
amzn.to/4oDGOq7 𝓒𝓸𝓷𝓽𝓮𝓷𝓽𝓼:
🔹Common Conventions & API Elements of Scikit-Learn
🔹Pre-Model Workflow and Data Preprocessing
🔹Dimensionality Reduction Techniques
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Linear Algebra and Optimization for Machine Learning [516-page textbook]: https://
amzn.to/39aWf8N
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This textbook is organized around its 2 main themes: [Amazon Summary] 1. Linear algebra and its applications: The chapters focus on the basics of linear algebra together with
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Building AI Intensive Python Applications — Create intelligent apps with LLMs and vector databases: https://
link.amazon/B05ZYiVMD
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Build Neo4j-Powered Applications with LLMs Available at https://
amzn.to/4l9lLKO This LLM book is for database developers and data scientists who want to leverage knowledge graphs with Neo4j and its vector search capabilities to build intelligent search and recommendation