Build Your Own AI Lab - Pearson

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Build Your Own AI Lab Introduction
  • 001. Build Your Own AI Lab Introduction.mp4 (12.3 MB)
Lesson 1 Introduction to AI Labs and Sandboxes
  • 001. Learning objectives.mp4 (9.4 MB)
  • 002. 1.1 Overview of AI Labs and Sandboxes Home-based vs. Cloud-based.mp4 (20.1 MB)
  • 003. 1.2 Choosing the Right Hardware (GPUs, CPUs, Memory, etc.).mp4 (50.3 MB)
  • 004. 1.3 Building or Buying Pre-built Systems.mp4 (15.2 MB)
  • 005. 1.4 Choosing the Operating Systems (Linux, Windows, macOS).mp4 (16.6 MB)
  • 006. 1.5 Surveying Essential Software (Python, Anaconda, Jupyter Notebooks, and Other Frameworks).mp4 (18.9 MB)
  • 007. 1.6 Introducing Hugging Face.mp4 (13.9 MB)
  • 008. 1.7 Introducing Ollama.mp4 (12.2 MB)
  • 009. 1.8 Installing Ollama.mp4 (16.5 MB)
  • 010. 1.9 Ollama Integrations.mp4 (46.9 MB)
  • 011. 1.10 Exploring the Ollama REST API.mp4 (12.7 MB)
  • 012. 1.11 Introducing Retrieval Augmented Generation (RAG).mp4 (13.9 MB)
  • 013. 1.12 Leveraging RAGFlow.mp4 (40.6 MB)
Lesson 2 Cloud-Based AI Labs and Sandboxes
  • 001. Learning objectives.mp4 (3.8 MB)
  • 002. 2.1 Advantages and Disadvantages of Cloud AI Labs and Sandboxes.mp4 (19.1 MB)
  • 003. 2.2 Introducing Amazon Bedrock.mp4 (21.0 MB)
  • 004. 2.3 Surveying Amazon SageMaker.mp4 (36.2 MB)
  • 005. 2.4 Exploring Google Vertex AI.mp4 (43.3 MB)
  • 006. 2.5 Using Microsoft Azure AI Foundry.mp4 (36.3 MB)
  • 007. 2.6 Discussing Cost Management and Security.mp4 (21.5 MB)
  • 008. 2.7 Using Terraform to Deploy Ollama in the Cloud.mp4 (10.4 MB)
Lesson 3 Integrating and Leveraging AI Environments
  • 001. Learning objectives.mp4 (4.5 MB)
  • 002. 3.1 Using Hybrid AI Labs Combining Home and Cloud Resources.mp4 (5.9 MB)
  • 003. 3.2 Synchronizing Data and Projects.mp4 (11.1 MB)
  • 004. 3.3 Leveraging the Strengths of Both Environments.mp4 (19.4 MB)
  • 005. 3.4 Running Open-Source Models Available on Hugging Face.mp4 (14.1 MB)
  • 006. 3.5 Introducing LangChain.mp4 (9.2 MB)
  • 007. 3.6 Introducing LlamaIndex.mp4 (7.5 MB)
  • 008. 3.7 Understanding Embedding Models.mp4 (31.9 MB)
  • 009. 3.8 Using Vector Databases.mp4 (17.4 MB)
Lesson 4 Advanced Topics
  • 001. Learning objectives.mp4 (3.7 MB)
  • 002. 4.1 Leveraging LangSmith and LangGraph.mp4 (14.6 MB)
  • 003. 4.2 Using Fine Tuning Frameworks.mp4 (17.1 MB)
  • 004. 4.3 High-Performance Computing and Edge AI.mp4 (11.8 MB)
Summary
  • 001. Build Your Own AI Lab Summary.mp4 (7.2 MB)

Description

Quote:

Build Your Own AI Lab



Published: 3/2024

Set up your own AI lab and infrastructure at home.

Hands-on guide to home and cloud-based AI labs and infrastructure
Learn to set up and optimize labs to research and experiment in a secure environment
Focused training on open-source large language models (LLMs) and generative AI
Build Your Own AI Lab covers how to create powerful and secure AI research environments. The course covers both home-based and cloud-based AI labs, offering comprehensive guidance on hardware and software setup, security best practices, cost management, and scalability. Key topics covered are how to run open-source models that can be accessed at Hugging Face, such as Llama 3, Phi 3, Mistral, Gemma, and other models; how to integrate and leverage the strengths of both environments, ensuring they have the flexibility to meet diverse research needs; and how to use Ollama to run these models easily in your home. It is an all-rounded resource with overview on Amazon Bedrock, Amazon SageMaker, Google Vertex AI, Microsoft Azure Cognitive Services, and high-performance computing and edge AI.



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Build Your Own AI Lab - Pearson

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Download torrent
666.6 MB
seeders:94
leechers:8
Build Your Own AI Lab - Pearson

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