there you have the concepts of multi-level models it' very advanced topicbut you need to understand what the concept isat leastand the concept itself is pretty simple you just are looking at the effects at different levelsdifferent hierarchies when you're trying to make prediction so maybe there are different layers of effects that have impacts on each otherand those different layers might have factors that interrelate with each other as well multilevel modeling tries to take account of all those different hierarchies and factors and how they interplay with each other rest assured that' all you need to know for now summary in this we talked about regression analysiswhich is trying to fit curve to set of training data and then using it to predict new values we saw its different forms we looked at the concept of linear regression and its implementation in python we learned what polynomial regression isthat isusing higher degree polynomials to create bettercomplex curves for multi-dimensional data we also saw its implementation in python we then talked about multivariate regressionwhich is little bit more complicated we saw how it is used when there are multiple factors affecting the data that we're predicting we looked at an interesting examplewhich predicts the price of car using python and very powerful toolpandas finallywe looked at the concept of multi-level models we understood some of the challenges and how to think about them when you're putting them together in the next we'll learn some machine learning techniques using python