Solving Real-World Data Science Problems with LLMs - Historical Document Analysis
Offered By: Keith Galli via YouTube
Course Description
Overview
Syllabus
- Video Overview & Reference Material
- Data & Code Setup
- Task #0: Configure LLM to use with Python OpenAI API
- Task #0 continued: LLM Configuration with Open-Source Model LLama 2 via Ollama
- Task #1: Use LLM to Parse Simple Sentence Examples
- Sub-task #1: Convert string to Python Object
- Task #1 continued: Use Open-Source LLM to Parse Sentence Examples w/ LangChain
- Quick note on a benefit of using LangChain easily switching between models
- Task #2 warmup: Grab Apprenticeship Agreement rows from Dataframe
- Task #2: Connect Pages that Belong to the Same Documents
- Task #3: Parse out values from merged documents
- Task #4 setup: Analyze Results
- Fixing up our results from task #3 quickly
- Task #4: Find the average age of apprentices in our merged contract documents
- Other analysis, wlho had the most apprentices?
Taught by
Keith Galli
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