Big Data Analytics

CSE545 - Spring 2019

Slides are intended as a visual aid for the lecture given in class. They are not a comprehensive set of class notes or a replacement for the readings.

• Topic 1: What is Big Data?
• Topic 2: Streaming Algorithms
• Topic 3: Hadoop: Distributed Architecture, HDFS, MapReduce
• Topic 4: Spark [ Example Code from 2-18 ]
• Topic 5: Distributed Tensorflow [ Example Tensorflow code from 3-4 ]
• Topic 6: Similarity Search
• Topic 7: Link Analysis
• Special Topic: Big Data and Social Science Applications
• Topic 8: Hypothesis Testing, ProbStat Preliminaries
• Topic 9: Supervised and Distributed Machine Learning
• Topic 10: Recommendation Systems
• Topic 11: Transformer Models

Slides from previous offerings of the class may be found here: Fall 2017, Fall 2016
Warning: some content from these slides may be outdated.