Build Neo4j-Powered Applications with LLMs Available at
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A Python Guide Covers Automation and Building AI Tools
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Python for Real Life — Code, Automate, and Build AI Tools — An All-in-One Guide to Learning Python Programming, Solving Real Problems, and Creating AI-Powered Apps (from the “Python for Real Life” Series) Get it here: https://
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Python Automation Recipes Cover MCP Integration and AI Workflows
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Python Automation Cookbook — 100+ new and updated recipes for scalable workflows, MCP integrations, and AI-powered automation: https://
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PostgreSQL 18 Guide Combines Vector Search, Analytics and Transactions
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New! 580 pages. From @PacktPublishing @PacktDataML "AI-Ready PostgreSQL 18 — Build Intelligent Data Systems with Transactions, Analytics, and Vectors" Available at https://
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A Tutorial Introduces Grok and Claude Workflows
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Grok AI Tutorial: From Zero to Pro (AI Made Easy Book 4) — https://
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See all the books in the “AI Made Easy” series, including “CLAUDE AI MASTERY: The Advanced Professional's Guide From Solid Fundamentals to Expert-Level AI Collaboration” — https://
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Python MLOps Guide Covers the Machine Learning Model Lifecycle
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Machine Learning Engineering with Python — Manage the lifecycle of machine learning models using MLOps with practical examples: https://
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Study Guide Explains Transformers and Large Language Models
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Super Study Guide: Transformers & Large Language Models: https://
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An Enterprise Generative AI Guide Covers Agent Context and Memory
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"Building Business-Ready Generative #AI Systems — Build Human-Centered Generative AI Systems with Context-Aware Agents, Memory, and LLMs for the Enterprise" at https://
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Graph Machine Learning Guide Uses PyTorch Geometric and Deep Graph Library
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Graph Machine Learning — the latest advancements in graph data to build robust machine learning algorithms. 2nd Edition at https://
amzn.to/45Y3LyI 𝓚𝓮𝔂 𝓕𝓮𝓪𝓽𝓾𝓻𝓮𝓼: Master new graph ML techniques through updated examples using PyTorch Geometric and Deep Graph Library -
Generative AI Guide Covers LLMs, Vector Databases, RAG, and Agents
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“Generative AI with Python: The Developer’s Guide to Pretrained LLMs, Vector Databases, Retrieval Augmented Generation, and Agentic Systems” Available at https://
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