Llms in Production - Brousseau, Christopher
56,99 €
inkl. MwSt.
Versandkostenfrei*
Versandfertig in über 4 Wochen
payback
28 °P sammeln
  • Gebundenes Buch

From the back cover: LLMs in Production is the comprehensive guide to LLMs you'll need to effectively guide you to production usage. It takes you through the entire lifecycle of an LLM, from initial concept, to creation and fine tuning, all the way to deployment. You'll discover how to effectively prepare an LLM dataset, cost-efficient training techniques like LORA and RLHF, and how to evaluate your models against industry benchmarks. Learn to properly establish deployment infrastructure and address common challenges like retraining and load testing. Finally, you'll go hands-on with three…mehr

Andere Kunden interessierten sich auch für
Produktbeschreibung
From the back cover: LLMs in Production is the comprehensive guide to LLMs you'll need to effectively guide you to production usage. It takes you through the entire lifecycle of an LLM, from initial concept, to creation and fine tuning, all the way to deployment. You'll discover how to effectively prepare an LLM dataset, cost-efficient training techniques like LORA and RLHF, and how to evaluate your models against industry benchmarks. Learn to properly establish deployment infrastructure and address common challenges like retraining and load testing. Finally, you'll go hands-on with three exciting example projects: a cloud-based LLM chatbot, a Code Completion VSCode Extension, and deploying LLM to edge devices like Raspberry Pi. By the time you're done reading, you'll be ready to start developing LLMs and effectively incorporating them into software. About the reader: For data scientists and ML engineers, who know Python and the basics of Kubernetes and cloud deployment.
Autorenporträt
Christopher Brousseau is a Staff MLE at JPMorganChase with a linguistics and localization background. He specializes in linguistically-informed NLP, especially with an international focus and has led successful ML and Data product initiatives at both startups and Fortune 500s. Matt Sharp is an engineer, former data scientist, and seasoned technology leader in MLOps. Has led many successful data initiatives for both startups and top-tier tech companies alike. Matt specializes in deploying, managing, and scaling machine learning models in production, regardless of what that production setting looks like.