Bayesian Inference: The Foundation of Data Science
DataCafé
English - March 23, 2021 06:00 - 42 minutes - 29.1 MBMathematics Science Education datacafé data science data analytics advanced analytics business intelligence optimisation machine learning artificial intelligence data engineering Homepage Download Google Podcasts Overcast Castro Pocket Casts RSS feed
In this episode we talk about all things Bayesian. What is Bayesian inference and why is it the cornerstone of Data Science?
Bayesian statistics embodies the Data Scientist and their role in the data modelling process. A Data Scientist starts with an idea of how to capture a particular phenomena in a mathematical model - maybe derived from talking to experts in the company. This represents the prior belief about the model. Then the model consumes data around the problem - historical data, real-time data, it doesn't matter. This data is used to update the model and the result is called the posterior.
Why is this Data Science? Because models that react to data and refine their representation of the world in response to the data they see are what the Data Scientist is all about.
We talk with Dr Joseph Walmswell, Principal Data Scientist at life sciences company Abcam, about his experience with Bayesian modelling.
Further Reading
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Recording date: 16 March 2021
Interview date: 26 February 2021
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