Learn Mistral : Elevating Mistral systems through embeddings, agents, RAG, AWS Bedrock, and Vertex AI
Unlock the power of Mistral models by building embeddings, RAG systems, and coding assistants that deliver real-world AI solutions. Every book comes with a PDF copy, AI Assistant, and Next-Gen Reader free. Key Features: Build secure local chat apps, multi-agent workflows, and coding assistants with...
Wedi'i Gadw mewn:
| Prif Awdur: | |
|---|---|
| Fformat: | Livre numérique |
| Iaith: | Anglais |
| Cyhoeddwyd: |
Birmingham :
Packt Publishing
2025.
Paris : Cyberlibris |
| Mynediad Ar-lein: | Accès Université d'Orléans et IFPM |
| Nodyn: |
Couverture. https://static2.cyberlibris.com/books_upload/300pix/9781835888650.jpg Cyberlibris (ScholarVox) corpus Informatique |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Learn Mistral, Elevating Mistral systems through embeddings, agents, RAG, AWS Bedrock, and Vertex AI, Pavlo Cherkashin, Birmingham, Packt Publishing, 2025, 1 vol. (528 p.), 978-18-3588-864-3 |
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| 245 | 1 | 0 | |a Learn Mistral : |b Elevating Mistral systems through embeddings, agents, RAG, AWS Bedrock, and Vertex AI |c Pavlo Cherkashin. |
| 260 | |a Birmingham : |b Packt Publishing. | ||
| 260 | |a Paris : |b Cyberlibris, |c 2025. | ||
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| 500 | |a Cyberlibris (ScholarVox) corpus Informatique | ||
| 506 | |a L'accès en ligne est réservé aux établissements ou bibliothèques ayant souscrit l'abonnement. Cyberlibris | ||
| 520 | |a Unlock the power of Mistral models by building embeddings, RAG systems, and coding assistants that deliver real-world AI solutions. Every book comes with a PDF copy, AI Assistant, and Next-Gen Reader free. Key Features: Build secure local chat apps, multi-agent workflows, and coding assistants with Mistral; Master embeddings and advanced RAG techniques to create scalable, context-aware AI; Deploy compliant, production-ready AI on AWS Bedrock, Google Vertex AI, and beyond. Book Description: This is a practical, project-driven guide to turning open-source Mistral models into production-ready AI solutions. Through hands-on workshops and use cases, you'll learn how to build private chat systems, semantic search engines, intelligent agents, coding assistants, and secure deployments that go beyond simple experimentation. The journey begins by exploring where Mistral excels and where human oversight is essential. You'll then learn to set up a secure, locally hosted chat system with Ollama, customize behavior with system prompts and parameters, and dive deep into embeddings to unlock semantic search with Pinecone. As you progress, you'll build multi-agent workflows, unpack advanced Retrieval-Augmented Generation pipelines, and integrate Mistral with Codestral to accelerate coding. You'll also learn to apply Mistral to cybersecurity, be challenged with open-ended RAG projects, and be guided through deploying scalable AI on AWS Bedrock and Google Vertex AI. By the end of this book, you will be ready to design and build AI systems that are innovative, compliant, and production-ready. What you will learn: Build a secure local chat system with Ollama and Mistral; Tune prompts and parameters to control model behavior; Use embeddings and Pinecone for semantic search systems; Design agents and multi-agent workflows with Mistral; Implement advanced Retrieval-Augmented Generation pipelines; Create coding copilots with Codestral in VS Code; Deploy scalable AI on AWS Bedrock and Google Vertex AI. Who this book is for: This book is ideal for software developers, AI practitioners, data scientists, and technology enthusiasts who are keen to master Mistral models. Whether you're looking to deploy powerful AI systems, enhance your existing skills, or understand the intricacies of operating AI in regulated environments, this book provides the knowledge and practical insights needed to excel | ||
| 776 | 0 | |t Learn Mistral |o Elevating Mistral systems through embeddings, agents, RAG, AWS Bedrock, and Vertex AI |f Pavlo Cherkashin |c Birmingham |n Packt Publishing |d 2025 |p 1 vol. (528 p.) |z 978-18-3588-864-3 | |
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