| 001. Build Your Own AI Lab Introduction.mp4 | 12.3 MB | ||
| 001. Build Your Own AI Lab Summary.mp4 | 7.2 MB | ||
| 001. Learning objectives.mp4 | 3.7 MB | ||
| 002. 1.1 Overview of AI Labs and Sandboxes Home-based vs. Cloud-based.mp4 | 20.1 MB | ||
| 002. 2.1 Advantages and Disadvantages of Cloud AI Labs and Sandboxes.mp4 | 19.1 MB | ||
| 002. 3.1 Using Hybrid AI Labs Combining Home and Cloud Resources.mp4 | 5.9 MB | ||
| 002. 4.1 Leveraging LangSmith and LangGraph.mp4 | 14.6 MB | ||
| 003. 1.2 Choosing the Right Hardware (GPUs, CPUs, Memory, etc.).mp4 | 50.3 MB | ||
| 003. 2.2 Introducing Amazon Bedrock.mp4 | 21 MB | ||
| 003. 3.2 Synchronizing Data and Projects.mp4 | 11.1 MB | ||
| 003. 4.2 Using Fine Tuning Frameworks.mp4 | 17.1 MB | ||
| 004. 1.3 Building or Buying Pre-built Systems.mp4 | 15.2 MB | ||
| 004. 2.3 Surveying Amazon SageMaker.mp4 | 36.2 MB | ||
| 004. 3.3 Leveraging the Strengths of Both Environments.mp4 | 19.4 MB | ||
| 004. 4.3 High-Performance Computing and Edge AI.mp4 | 11.8 MB | ||
| 005. 1.4 Choosing the Operating Systems (Linux, Windows, macOS).mp4 | 16.6 MB | ||
| 005. 2.4 Exploring Google Vertex AI.mp4 | 43.3 MB | ||
| 005. 3.4 Running Open-Source Models Available on Hugging Face.mp4 | 14.1 MB | ||
| 006. 1.5 Surveying Essential Software (Python, Anaconda, Jupyter Notebooks, and Other Frameworks).mp4 | 18.9 MB | ||
| 006. 2.5 Using Microsoft Azure AI Foundry.mp4 | 36.3 MB | ||
| 006. 3.5 Introducing LangChain.mp4 | 9.2 MB | ||
| 007. 1.6 Introducing Hugging Face.mp4 | 13.9 MB | ||
| 007. 2.6 Discussing Cost Management and Security.mp4 | 21.5 MB | ||
| 007. 3.6 Introducing LlamaIndex.mp4 | 7.5 MB | ||
| 008. 1.7 Introducing Ollama.mp4 | 12.2 MB | ||
| 008. 2.7 Using Terraform to Deploy Ollama in the Cloud.mp4 | 10.4 MB | ||
| 008. 3.7 Understanding Embedding Models.mp4 | 31.9 MB | ||
| 009. 1.8 Installing Ollama.mp4 | 16.5 MB | ||
| 009. 3.8 Using Vector Databases.mp4 | 17.4 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 | ||
| ▲ 36 total files | |||
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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