Industry-relevant training in Business, Technology, and Design to help professionals and graduates upskill for real-world careers.
Fun, engaging games to boost memory, math fluency, typing speed, and English skillsβperfect for learners of all ages.
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What do nodes and edges represent in a graphical model?
π‘ Hint: Think about what connects the variables in the graph.
Question 2
Easy
What is a Bayesian Network?
π‘ Hint: Reflect on how the directionality plays a role in the model.
Practice 4 more questions and get performance evaluation
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
What do graphical models primarily represent?
π‘ Hint: Consider what a graphical representation would entail in terms of probabilities.
Question 2
Bayesian Networks are based on which type of graphs?
π‘ Hint: Think about the directionality of edges in these models.
Solve 2 more questions and get performance evaluation
Push your limits with challenges.
Question 1
Design a simple Bayesian Network for a basic weather forecasting model considering rain, humidity, and temperature. Define the conditional dependencies.
π‘ Hint: Consider how one weather condition affects others.
Question 2
Explain how you would use a Markov Random Field for image classification.
π‘ Hint: Think about the influence of adjacent pixels in an image.
Challenge and get performance evaluation