What Are Bayesian Networks In Python? - The Friendly Statistician

Описание: What Are Bayesian Networks In Python? In this informative video, we will introduce you to Bayesian networks in Python, a powerful approach to managing uncertainty in data analysis. We will discuss the basics of Bayesian networks, including their structure and how they represent relationships between variables. You will learn about the directed acyclic graphs that form the foundation of these networks and how they help in encoding probability distributions.

We'll guide you through the process of implementing Bayesian networks using the pgmpy library in Python. You will see how to construct the network, define conditional probability tables, and fit the model to your data. Additionally, we will cover how to perform inference to update probability estimates based on new information.

Bayesian networks have a wide range of applications, from medical diagnosis to risk assessment and decision-making. By incorporating prior knowledge and observed data, these networks provide a systematic way to make informed predictions and decisions under uncertainty.

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