This repository contains a collection of my work in Artificial Intelligence and Machine Learning. Each project focuses on applying core ML techniques to real-world datasets using Python and Jupyter Notebooks.
These projects demonstrate skills in:
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Data cleaning, preprocessing, and visualization
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Model training, evaluation, and optimization
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Working with libraries such as NumPy, Pandas, scikit-learn, and Matplotlib
This project uses a manually labeled Airbnb Reviews dataset to train and evaluate sentiment classification models.
Due to GitHub’s file size limits, the dataset is hosted externally.
📎 Access the dataset here: [Airbnb Reviews Labeled Dataset (CSV) link: https://drive.google.com/file/d/17ImqNI7_7WK5s-sJp2OTsJZQ8Oi2whGv/view?usp=share_link
Details:
- Contains user-generated Airbnb reviews with manually annotated sentiment labels (positive, negative, neutral)
- Used for supervised training and performance benchmarking
- Cleaned and preprocessed in Jupyter Notebook before modeling