AI on-prem deployment.

Format:

Video

Contributor:

Vugt, Sander van, instructor.

Pearson (Firm), publisher.

Language:

English

Subjects (All):

Generative artificial intelligence.

Natural language generation (Computer science).

Physical Description:

1 online resource (1 video file (4 hr., 50 min.)) : sound, color.

Edition:

[First edition].

Place of Publication:

[Place of publication not identified] : Pearson, 2026.

Summary:

Master onpremises GenAI: deploy; optimize; and finetune LLMs on Linux and Kubernetes to deliver private; highperformance AI; without sending your data to the cloud. Deploy private GenAI on your own infrastructure: Understand GenAI fundamentals and core components, choose the right LLM, and run models locally for control over data, privacy, performance, and cost. Build and optimize on Linux: Configure GPU drivers and container GPU support, tune CPU/GPU inference, and run inference servers (llama.cpp and vLLM) on platforms with or without GPU, with an accessible client experience using OpenWebUI. Production-ready workflows with Kubernetes: Add proprietary documents using RAG, prepare and run GenAI on Kubernetes (GPU workloads and non-GPU, storage, access, scaling/monitoring), and complete an end-to-end deployment that ties everything together.

Notes:

OCLC-licensed vendor bibliographic record.

ISBN:

9780135894217

OCLC:

1615392691