Data Science Course Assignments

This repository contains the notebooks for the DS2024 data science course labs.

Contents

• Lab1.ipynb - Web scraping lab focused on collecting hotel accommodation data from Booking, Trivago, and Agoda. It includes Selenium/BeautifulSoup setup, scraping utilities, data collection, exploratory data analysis, and a small interactive filtering workflow.
• Lab2.ipynb - Modeling lab focused on exploratory analysis, normalization, transformations, dimensionality reduction, and regression model comparison. It includes PCA, ICA, linear regression, random forest, SVR, evaluation metrics, and visualizations.

Methods Used

• Web scraping with Selenium and BeautifulSoup.
• Data cleaning and tabular processing with pandas.
• Exploratory data analysis using summary statistics and visualizations.
• Interactive filtering with ipywidgets.
• Feature scaling and normalization.
• Correlation analysis and distribution transformation.
• Dimensionality reduction with Principal Component Analysis and Independent Component Analysis.
• Regression modeling with linear regression, random forest, support vector regression, and decision tree-based approaches.
• Model evaluation using MAE, MSE, RMSE, R2, residual plots, and actual-versus-predicted visualizations.