YoVDO

Advanced Python Projects: Build AI Applications

Offered By: LinkedIn Learning

Tags

Artificial Intelligence Courses Machine Learning Courses Python Courses Chatbot Courses Sentiment Analysis Courses Matplotlib Courses pandas Courses scikit-learn Courses Data Analytics Courses

Course Description

Overview

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Learn the skills and knowledge needed to create a portfolio of Python-based applications and tools that can be showcased to employers or used to bring your own ideas to life.

Syllabus

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
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
Conclusion
  • Your next steps

Taught by

Priya Mohan

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