Here Student Performance Data Set dataset by Data-Science Sean is used to perform EDA
and create a machine learning model
that can predict student's final grades i.e. Tthe goal is to predict G3
using G1
and G2
.
The notebook is available on Kaggle to work in the same environment where this notebook was created i.e. use the same version packages used, etc...
age
has low positive correlation withfailure
Medu
&Fedu
has moderate positive correlation & they both have low positive correlation withgrades
studytime
&grades
have a low positive correlation
failure
has low negative correlation withgrades
freetime
has low positive correlation withgoout
goout
has low positive correlation withWalc
Walc
has moderate positive correlation withDalc
and they both have negligible negative correlation
Learning curve
Loss and R2 square metrics
Actual Vs Predicted values