Artículo: AMZ-B0FGCFZQW8

LLMs for Anomaly Detection: A Practical Applications for Enhancing Data Security and Monitoring

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How LLMs are revolutionizing anomaly detection: From text analysis to complex data transformation, learn how these AI models are changing the game for detecting fraud, system errors, and security breaches.
Practical, real-world applications: Dive into case studies like LogPrompt, SIGLLM, and PyOD 2, and see how LLMs are used to tackle some of the toughest challenges in cybersecurity and data integrity.
How multi-agent systems are making anomaly detection more scalable and efficient: Discover how autonomous agents powered by LLMs collaborate seamlessly to monitor, detect, and resolve anomalies across complex data environments.
The power of LLMs in providing detailed, human-readable explanations: No more confusion—learn how LLMs explain the “why” behind anomalies, enabling faster, more accurate decision-making.
Data augmentation, intelligent model selection, and more: Uncover how LLMs can generate synthetic data, automate model selection, and ensure your anomaly detection systems are always performing at their best.
Step-by-step insights: Whether you're a data scientist, cybersecurity expert, or business leader, this book gives you clear, actionable insights that can immediately be applied to your work.
Unlock the full potential of LLMs: Learn how to leverage the full power of AI in anomaly detection—without being a machine learning expert.
Boost your data security: With real-world examples, you’ll learn how LLMs enhance your system’s ability to detect anomalies before they turn into costly problems.

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LLMs for Anomaly Detection: A Practical Applications for Enhancing Data Security and Monitoring

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LLMs for Anomaly Detection: A Practical Applications for Enhancing Data Security and Monitoring

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Otros Productos

Build a Large Language Model (From Scratch)

Hands-On Large Language Models: Language Understanding and Generation

AI Engineering: Building Applications with Foundation Models

LLM Engineer's Handbook: Master the art of engineering large language models from concept to production

Building AI Agents with LLMs, RAG, and Knowledge Graphs: A practical guide to autonomous and modern AI agents

The Agentic AI Bible: The Complete and Up-to-Date Guide to Design, Build, and Scale Goal-Driven, LLM-Powered Agents that Think, Execute and Evolve

Prompt Engineering for LLMs: The Art and Science of Building Large Language Model-Based Applications

Building LLMs for Production: Enhancing LLM Abilities and Reliability with Prompting, Fine-Tuning, and RAG

The Hundred-Page Language Models Book: hands-on with PyTorch (The Hundred-Page Books)

Large Language Models: A Deep Dive: Bridging Theory and Practice

LLM Design Patterns: A Practical Guide to Building Robust and Efficient AI Systems

Designing Large Language Model Applications: A Holistic Approach to LLMs

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