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Unlock the power of AWS Bedrock and build cutting-edge generative AI applications today!
In this comprehensive video, you'll learn step-by-step how to create end-to-end AI projects using Amazon Bedrock's robust foundation models like Llama 2, Jurassic-2, and more. Whether you're a beginner or an experienced developer, this video simplifies complex concepts and makes AI development accessible to everyone.
What you'll discover:
- How to set up and authenticate AWS Bedrock on your account.
- Practical guidance for using foundation models for text generation, summarization, and image creation.
- The process of implementing Retrieval-Augmented Generation (RAG) with real-world examples.
- Creating scalable, production-ready AI applications optimized for fast inference.
Key highlights:
- Demonstration of various models.
- Hands-on coding walkthrough using Python and tools like LangChain, Streamlit .
- Best practices for deploying generative AI apps in AWS environments.
Ready to kickstart your generative AI journey? Hit play and code along! Don’t forget to Like, Subscribe, and hit the notification bell for more tutorials. Let’s innovate together with AWS Bedrock!
#aiautomation #aibusinessideas #aiautomationbusiness #awscli #amazonbedrock
CHAPTERS:
00:00 - Introduction
00:45 - Accessing Amazon Bedrock
02:06 - Getting Started with Amazon Bedrock
05:36 - Creating an IAM User
07:20 - Installing AWS CLI
08:21 - Setting up the project
11:17 - Creating the project structure
14:00 - Tools and technologies
16:54 - Installing the requirements
18:09 - Testing the Bedrock platform
21:16 - End to End Demo of Amazon Bedrock
23:30 - Creating Basic UI using Streamlit
25:34 - Creating LLM Wrapper
27:05 - Creating the Chatbot Function
30:21 - Creating the Streamlit UI
33:14 - Running the Bedrock Client
34:50 - Testing the Bedrock Client
36:47 - End to End RAG Pipeline Architecture
42:35 - Coding RAG Pipeline
44:19 - Creating the Prompt Template
45:22 - Extracting the Documents
47:20 - Creating the Vector Store
48:28 - Creating the Response Function
49:40 - Creating the User Application
56:55 - Common Deployment Pipeline
1:00:25 - Deployment Steps
1:00:54 - Creating an EC2 Instance
1:02:06 - Connecting to EC2 Instance
1:03:00 - Updating and Installing Docker
1:05:00 - Building Docker Image
1:06:40 - Running Docker Image
1:07:52 - Terminating EC2 Instance
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