Distributed AI Systems — A practical guide to building scalable training, inference, and serving systems for production AI: https://
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Find more best-selling AI/ML books by @PacktPublishing @PacktDataML here: https://
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Distributed AI Systems Guide Covers Training, Inference and Serving
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Agentic AI Guide Covers Automated Penetration Testing Workflows
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Agentic AI for Offensive Cybersecurity — Build and Automate Smarter Penetration Testing Workflows using AI-driven Agents: https://
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Python Data Analysis Guide Adds Machine Learning and Generative AI
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"Python Data Analysis: Master Python Analytics with Machine Learning, Deep Learning, GenAI, LLMs, and Data Engineering" [4th Edition] Available at https://
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LLM Engineering Handbook Covers Data Pipelines and Training Cycles
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LLM Engineer's Handbook — Master the art of engineering Large Language Models LLMs from concept to production: https://
amzn.to/4dUQrv6 v/ @PacktDataML @PacktPublishing Implement robust data pipelines and manage LLM training cycles
Create your own LLM and refine with the help -
Context Engineering Guide Covers Memory for Multi-Agent Systems
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"Context Engineering for Multi-Agent Systems: Move beyond prompting to build a Context Engine, a transparent architecture of context and reasoning" — at https://
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Develop memory models to retain short-term and -
Generative AI Guide Covers Graph RAG, Memory and Intelligent Recall
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"Unlocking Data with Generative AI and RAG — Learn AI Agent Fundamentals with RAG-powered Memory, Graph-based RAG, and Intelligent Recall" Get it here: https://
amzn.to/49zsIkb 2nd Edition, by @keithbourne v/ @PacktDataML -
Guide Distinguishes Coding Assistants From AI Agents and Workflows
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Code Revealed — A practical guide to AI agents, workflows, and modern application practices: https://
amzn.to/45I2kCU via @PacktPublishing @PacktDataML 𝓦𝓱𝓪𝓽 𝓨𝓸𝓾 𝓦𝓲𝓵𝓵 𝓛𝓮𝓪𝓻𝓷:
Distinguish agents from simpler AI coding assistants
Assess tool fit using capability -
DeepSeek Guide Covers Fine-Tuning, Distillation and Agent Design
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"DeepSeek in Practice: From basics to fine-tuning, distillation, agent design, and prompt engineering of open source LLM" at https://
amzn.to/4imbryH v/ @PacktDataML Discover DeepSeek's unique traits in the LLM landscape
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A Python Guide Builds Explainable Models and Debugs Bias
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Develop and Debug high-performance, low-bias, and explainable Machine Learning and Deep Learning Models with Python : https://
amzn.to/3u2JiIB by @AliMLearning via @PacktDataML —————
#DataScientist #DataScience #ML -
LlamaIndex Guide Covers RAG Pipelines and Agent Workflows
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Build Data-Driven Applications with LlamaIndex — Practical guide to RAG pipelines, agentic workflows, and production AI deployment [2nd Edition]: https://
amzn.to/4zhNsZR via @PacktDataML @PacktPublishing