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LLM Engineer’s Handbook (2024)

🚀 Unlock the Future of AI with the LLM Engineer’s Handbook 🚀

Step into the world of Large Language Models (LLMs) with this comprehensive guide that takes you from foundational concepts to deploying advanced applications using LLMOps best practices. Whether you're an AI engineer, NLP professional, or LLM enthusiast, this book offers practical insights into designing, training, and deploying LLMs in real-world scenarios.

Why Choose the LLM Engineer’s Handbook?

Comprehensive Coverage: Learn about data engineering, supervised fine-tuning, and deployment strategies.

Hands-On Approach: Implement MLOps components through practical examples, including building an LLM-powered twin that's cost-effective, scalable, and modular.

Cutting-Edge Techniques: Explore inference optimization, preference alignment, and real-time data processing to apply LLMs effectively in your projects.

Real-World Applications: Move beyond isolated Jupyter notebooks and focus on building production-grade end-to-end LLM systems.


Limited-Time Offer

Originally priced at $55, the LLM Engineer’s Handbook is now available for just $25—a 55% discount! This special offer is available for a limited quantity, so act fast to secure your copy.

Who Should Read This Book?

This handbook is ideal for AI engineers, NLP professionals, and LLM engineers looking to deepen their understanding of LLMs. A basic knowledge of LLMs, Python, and AWS is recommended. Whether you're new to AI or seeking to enhance your skills, this book provides comprehensive guidance on implementing LLMs in real-world scenarios.

Don't miss this opportunity to advance your expertise in LLM engineering. Secure your discounted copy today and take the next step in your AI journey!

Buy book: https://www.patreon.com/DataScienceBooks/shop/llm-engineers-handbook-2024-1582908



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LLM Engineer’s Handbook (2024)

🚀 Unlock the Future of AI with the LLM Engineer’s Handbook 🚀

Step into the world of Large Language Models (LLMs) with this comprehensive guide that takes you from foundational concepts to deploying advanced applications using LLMOps best practices. Whether you're an AI engineer, NLP professional, or LLM enthusiast, this book offers practical insights into designing, training, and deploying LLMs in real-world scenarios.

Why Choose the LLM Engineer’s Handbook?

Comprehensive Coverage: Learn about data engineering, supervised fine-tuning, and deployment strategies.

Hands-On Approach: Implement MLOps components through practical examples, including building an LLM-powered twin that's cost-effective, scalable, and modular.

Cutting-Edge Techniques: Explore inference optimization, preference alignment, and real-time data processing to apply LLMs effectively in your projects.

Real-World Applications: Move beyond isolated Jupyter notebooks and focus on building production-grade end-to-end LLM systems.


Limited-Time Offer

Originally priced at $55, the LLM Engineer’s Handbook is now available for just $25—a 55% discount! This special offer is available for a limited quantity, so act fast to secure your copy.

Who Should Read This Book?

This handbook is ideal for AI engineers, NLP professionals, and LLM engineers looking to deepen their understanding of LLMs. A basic knowledge of LLMs, Python, and AWS is recommended. Whether you're new to AI or seeking to enhance your skills, this book provides comprehensive guidance on implementing LLMs in real-world scenarios.

Don't miss this opportunity to advance your expertise in LLM engineering. Secure your discounted copy today and take the next step in your AI journey!

Buy book: https://www.patreon.com/DataScienceBooks/shop/llm-engineers-handbook-2024-1582908

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The campaign, which security firm Check Point has named Rampant Kitten, comprises two main components, one for Windows and the other for Android. Rampant Kitten’s objective is to steal Telegram messages, passwords, and two-factor authentication codes sent by SMS and then also take screenshots and record sounds within earshot of an infected phone, the researchers said in a post published on Friday.

A Telegram spokesman declined to comment on the bond issue or the amount of the debt the company has due. The spokesman said Telegram’s equipment and bandwidth costs are growing because it has consistently posted more than 40% year-to-year growth in users.

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