A data analytics enthusiast; interested in time series analysis, causal inference, and natural language processing.
"How to know whether any change exists? Using proper approach, you can make better inference; who knows that you've successfully reduced your boba intake?"
I am currently working as a Data Scientist at Airy, with experience in end to end data projects: data collection, data warehousing, visualization, statistical analysis, and machine learning. My interests are causal inference and natural language processing.
The goal of this session is to share how to identify **when** any change occurs in your data.
It will start with an explanation of change point analysis and some of the available techniques.
To make it more practical, there will be a demonstration of how to implement **single change point analysis** using the cumulative sum approach, mean squared error, and Bayesian approach (if the time is still available).