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Unlock the secrets to building a career-boosting AI Chatbot in this comprehensive video! Whether you're coding for beginners or enhancing your skills, this video is packed with practical insights to help you kickstart your programming journey. Perfect for beginners, you'll master Python fundamentals while exploring how to create a medical AI chatbot using cutting-edge tools like Pinecone vector databases, OpenAI models, and Flask for web development.
What you'll learn:
- How to build a chatbot using Python, custom medical datasets, and large language models.
- Step-by-step guidance on implementing semantic search with Pinecone and vector embeddings.
- Master the deployment process using AWS, Docker, and CI/CD pipelines for real-world applications.
- Tips for creating a user-friendly interface and scalable architecture.
This video is designed to make complex concepts approachable and actionable. You'll not only gain hands-on experience but also sharpen your programming skills, setting you up for career growth in AI and software development.
Ready to code along? Hit play and start building your AI chatbot today! Don’t forget to Like, Subscribe, and hit the notification bell to stay updated on more tutorials from EuronTech. Let’s turn your programming goals into reality!
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CHAPTERS:
00:00 - Introduction
00:19 - Using Medical Data
00:40 - Creating Knowledge Base
06:10 - Frontend Component Development
06:57 - Utilizing OpenAI Model
11:05 - Setting Up GitHub Repository
13:55 - Creating Virtual Environment
16:40 - Project Folder Structure Setup
19:52 - Listing Files and Folders
23:32 - Creating Folders and Files
25:44 - Handling OS Path Issues
31:31 - Implementing Project in Jupyter Notebook
33:38 - Modular Coding Implementation
36:17 - Downloading Hugging Face Embedding Model
37:36 - Creating Pinecone Index
42:12 - Pinecone Index Creation with Python
44:35 - Storing Vector Embeddings in Pinecone
47:50 - Loading Existing Pinecone Index
49:29 - Initializing OpenAI API
51:30 - Prompt Template Creation and Pinecone Integration
54:31 - End-to-End Project Implementation
56:14 - Creating Store Index Do File
1:00:22 - Creating Endpoint
1:09:23 - Medical Chatbot Deployment on AWS
1:11:35 - AWS Cloud Deployment Architecture Overview
1:17:05 - High-Level Deployment Architecture
1:19:59 - Deployment Steps Overview
1:20:01 - Preparing Files for Deployment
1:23:05 - Creating AWS Resources
1:26:10 - Setting Up EC2 Instance
1:28:16 - Configuring EC2 Instance
1:29:23 - Connecting EC2 to GitHub
1:31:38 - Setting Up GitHub Secrets
1:34:15 - Pushing Code and CI/CD Pipeline Check
1:36:08 - Testing Deployed Chatbot
1:38:10 - Terminating Resources
1:39:35 - Next Project Overview
1:39:49 - Conclusion and Goodbye
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