Text Classification Algorithm Comparison

[Cgarg9]

Description:

To help users understand different text classification approaches, add a notebook that applies multiple methods on the same dataset and compares results.

Tasks:

• Compare Naïve Bayes, Logistic Regression, Random Forest, LSTMs, and Transformer models (e.g., BERT, DistilBERT, GPT) for text classification.
• Provide performance metrics (accuracy, F1-score, confusion matrix).
• Summarize the best-suited methods for different datasets.
• Name the notebook text_classification_comparison.ipynb.
• Update the README file with relevant resources.

[Amisha2700]

@Cgarg9 please assign me this issue

[Cgarg9]

@Amisha2700 any progress?