Mining Massive Databases

Course topics

Part 1. Introduction to Big Data

• The general overview of the course
• Hadoop and spark introduction
• Pig and Pyspark comparison
• Public (big) datasets and resources

Part 2. Processing Structured and Semi-structured large data

• Preprocessing User Generated Content and other semi-structured data
• Introduction to PySpark
• Scikit-learn at large scale
• Basics of machine learning with pySpark

Part 3. Graphs

• Introduction to graphs
• Temporal graphs representation
• Centrality measures for graphs (PageRank, Hits, etc)
• Large graphs with NoSql databases. Communities / Clusters / Cliques in Graphs

Part 4. Working with Data Streams

• Data Streams, how are they different from static data?
• Online vs Offline Algorithms
• Applied ML in (large) streams

Prerequisites

• Machine Learning