Mining of Big Datasets

Exercise Solutions & Implementations

This repository contains my solutions for the Mining of Big Datasets course.
The work focuses on large‑scale data processing, similarity search, data streams, frequent itemsets, and distributed computation using Python, PySpark, and related tools.
To get started with the exercises, check out the Getting Started Guide

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Topics Covered

• MapReduce & distributed computation
• PySpark programming
• Locality-Sensitive Hashing (LSH)
• Mining data streams
• Frequent itemset mining
• Link analysis fundamentals
• Large‑scale similarity search
• Algorithmic analysis & reporting

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Repository Structure

Each folder includes:

• Code implementations
• Outputs and visualizations (if applicable)
• Written analysis and answers

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Technologies Used

• Python
• PySpark
• Jupyter Notebook
• Hashing & similarity algorithms
• Stream processing techniques

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Notes

• This repository contains only my own exercise solutions and code.
• No confidential course materials or restricted content are included.
• All implementations are for learning and demonstration purposes.