A collection of Jupyter notebooks for AI and ML tasks. Explore, learn, and contribute to advance your skills in artificial intelligence and machine learning. #Hacktoberfest friendly!
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Text classification using ML approach to detect spams #10
Advanced Features
You can enhance this code with the following features:
Hyperparameter Tuning: Optimize the model's performance by tuning hyperparameters.
Cross-Validation: Implement cross-validation for more robust evaluation.
Feature Engineering: Experiment with different text preprocessing techniques, such as TF-IDF, word embeddings, or pre-trained language models.
Visualization: Visualize model performance and data distributions using libraries like Matplotlib or Seaborn.
Error Analysis: Understand common misclassifications made by the model to improve its accuracy.
Advanced Models: Explore more advanced models like Support Vector Machines, Random Forests, or neural networks to improve classification performance.