Advanced Python Projects: Build AI Applications

Introduction

• Elevate Your Python portfolio with advanced AI applications
• What should you know before taking this course
• Using GitHub Codespaces with this course
• A refresher of object-oriented programming concepts

1. NLP: Build a Chatbot with Sentiment Analyzer

• Processing user input
• Analyzing sentiment
• Displaying automated chatbot responses based on sentiment
• Tailoring chatbot response based on sentiment score
• Intiating the chatbot and printing sentiment-based responses

2. Machine Learning: Using Python to Find Your Next Business Opportunity

• Data analytics using pandas, matplotlib, and scikit-learn
• Data preprocessing and scaling
• Model selection
• Hyperparameter tuning
• Linear regression, random forest, and gradient boosting
• Predicting price based on model evaluation results

3. Chat with Your Documents Using LLM: Back-end with OpenAI, Python, AWS, and FastAPI

• Setting up MongoDB
• Generate chat responses using GPT-3.5 and Langchain
• Load conversation history for a given session ID
• Create new sessions and add chat history to existing sessions
• Setup FastAPI app, CORS, S3 session, and obtain a chat response
• Upload files to Amazon S3 storage bucket
• Deploy and run the chatbot
• Challenge: Complete the backend code for file upload
• Solution: Complete the backend code for file upload

4. Chat with Your Documents Using LLM: Front-end with Streamlit

• Introduction to API communication with Python
• File uploads and advanced API interactions
• Streamlit app basics and file handling
• Uploading files to API endpoints with Streamlit
• Building a chat interface with Streamlit
• How to run the front end of the chatbot
• Challenge: Create a front-end UI for file upload
• Solution: Create a front-end UI for file upload

Conclusion

• Your next steps