Completed
- Task #3: Parse out values from merged documents
Class Central Classrooms beta
YouTube videos curated by Class Central.
Classroom Contents
Solving Real-World Data Science Problems with LLMs - Historical Document Analysis
Automatically move to the next video in the Classroom when playback concludes
- 1 - Video Overview & Reference Material
- 2 - Data & Code Setup
- 3 - Task #0: Configure LLM to use with Python OpenAI API
- 4 - Task #0 continued: LLM Configuration with Open-Source Model LLama 2 via Ollama
- 5 - Task #1: Use LLM to Parse Simple Sentence Examples
- 6 - Sub-task #1: Convert string to Python Object
- 7 - Task #1 continued: Use Open-Source LLM to Parse Sentence Examples w/ LangChain
- 8 - Quick note on a benefit of using LangChain easily switching between models
- 9 - Task #2 warmup: Grab Apprenticeship Agreement rows from Dataframe
- 10 - Task #2: Connect Pages that Belong to the Same Documents
- 11 - Task #3: Parse out values from merged documents
- 12 - Task #4 setup: Analyze Results
- 13 - Fixing up our results from task #3 quickly
- 14 - Task #4: Find the average age of apprentices in our merged contract documents
- 15 - Other analysis, wlho had the most apprentices?
