Bayesian Networks Finally Make Sense When You Stop Separating Graphs and Probability

1. 1Understand the basics of Bayesian Networks and their components
2. 2Learn how to encode dependencies using Directed Acyclic Graphs (DAGs)
3. 3Apply Bayes' theorem to update probabilities in the network
4. 4Visualize the network to identify key relationships and dependencies
5. 5Use Bayesian Networks to make predictions and update probabilities based on new data

Data scientists and machine learning engineers can benefit from this concept to improve their models and predictions, by understanding how to encode dependencies in Bayesian Networks

💡 Bayesian Networks are not just graphs or probability formulas, but a combination of both to encode dependencies and make predictions

📈 Improve your understanding of Bayesian Networks by combining graphs and probability to encode dependencies! #BayesianNetworks #MachineLearning