Guess what,
I was able to get a 98.7% accuracy on the model at the end of the day.
Here is the link
performanceindex.streamlit.app
And the also, you can check the code here,
github.com/Codaks-py/Stud… https://t.co/U8tKNgRWPZ
I did a thing.
This is a house pricing model that has a percentage error of 2.39% using stacked modelling techniques.
The stack model includes:
1️⃣Base model: Ridge, random forest regressor and XGBoost
2️⃣ meta model: Lasso
Check out the repo: github.com/Codaks-py/hous…
Added something to my github, hopefully i get to upload more there soon.
github.com/Codaks-py/Stud…
So what's the model on?
A simple model that predicts the student performance index based in variables that include 'Hours Studied', 'Previous Scores', 'Extracurricular Activities',
#dataAnalytics #Python#data
1/3
I came across a library called Pyforest, Pyforest makes working on dataset easier by replacing the part where you have to import the libraries needed to work on a particular data which include pandas, numpy, matplotlib and seaborn.
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