📅 2025-03-06 — Session: Data and File Management Session
🕒 17:00–20:05
🏷️ Labels: Data Processing, File Management, Text Embeddings, Redundancy Cleanup
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The primary objective of this session was to enhance data processing capabilities and manage file redundancies effectively.
Key Activities
- Dataframe Segmentation: Segmented text fields into 1000-character chunks for efficient text processing.
- Batch Encoding for Text Embeddings: Implemented batch encoding to improve text embedding efficiency.
- Duplicate File Management: Utilized command-line tools like
fdupesfor identifying and managing duplicate files. - Mathematical Content Analysis: Analyzed redundancy in mathematical formulas and file paths to suggest cleanup strategies.
- Gedit Troubleshooting: Addressed common issues with Gedit settings.
- Variance and Firm Size Analysis: Conducted in-depth analysis on variance decay and firm dynamics.
- Text Overlap and Redundancy Cleanup: Proposed strategies for consolidating overlapping content and centralizing figures.
Achievements
- Established a structured approach for text segmentation and embedding.
- Identified and proposed solutions for file redundancy issues.
- Enhanced understanding of variance decomposition in economic contexts.
Pending Tasks
- Implement the proposed cleanup strategies for file management.
- Further refine text embedding processes using AI techniques.