Merge pull request #34 from Quantum-Software-Development/FabianaCampanari-patch-1

Improve README with clearer explanations and examples

Author: FabianaCampanari

README.md

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 ## Overview
 
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 This repository demonstrates **dictionary-based feature grouping** for tabular data preprocessing, specifically designed for integration with **Large Language Models (LLMs)** and AI/ML pipelines.
 
 The technique allows you to organize related columns (features) in a dataset using **dictionaries**, enabling:
 
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 - Semantic grouping of features
 -  Efficient preprocessing for LLM-based feature engineering
 -  Better interpretability of tabular data
 -  Streamlined data transformation pipelines
 
 
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 ##  What is Dictionary-Based Feature Grouping?
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 ### 💡 Simple Explanation (For Beginners)
 
 Imagine you have a dataset about customers with many columns:
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 ```
 age, income, city, state, country, purchase_date, product_name, price, ...
 ```
 
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 Instead of processing all columns individually, you can **group them** by meaning:
 
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 ```python
 feature_groups = {
     'demographics': ['age', 'income'],
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 This makes it easier to:
 
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 1. Apply specific transformations to each group
 2. Feed organized data to LLMs
 3. Understand your dataset structure