In this post, I would like to focus more on the Bayesian Linear Regression theory and implement the modelling in Python for a data science project. The whole project is about forecasting urban water consumption under the impact of climate change in the next three decades. The complete version of the code is available as a Jupyter Notebook on GitHub and I encourage you to check it out. Also, the result is published in Sustainable Cities and Societies.

Why Bayesian Statistics?

Statistics have two main branches, descriptive statistics and inferential statistics. Descriptive statistics provide a concise summary of data, while inferential statistics find patterns and make inferences about the data. But why am I talking about these two terms? 😀 Well, there are two general “philosophies” in inferential statistics that are important for us; frequentism and Bayesianism.

#machine-learning #python #predictive-analytics