Transform messy Telegram posts into a smart FinTech engine that reveals which vendors are the best candidates for a loan.
# 🛒 Amharic E-commerce Data Extractor for EthioMart
## 🔍 Project Overview
This project develops a **smart FinTech engine** that transforms unstructured Telegram messages into structured business data — helping EthioMart identify the most promising vendors for micro-lending.
I build a Named Entity Recognition (NER) system to extract:
- 📦 Product Names
- 💰 Prices
- 📍 Locations and so on ...
from **Amharic text, images, and documents** shared across multiple Telegram channels.
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## 🎯 Project Goals
1. **Automate Telegram Data Extraction** from 5+ e-commerce channels.
2. **Fine-Tune NER Models** (XLM-R, AfroXLMR, mBERT) on labeled Amharic text.
3. **Evaluate & Interpret** model predictions with SHAP/LIME.
4. **Score Vendors** based on business activity, engagement, and pricing.
5. **Support Micro-Lending** through a data-driven vendor analytics engine.
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