Assumptions of Linear Regression with Python
A lot of us stop once we have created a Linear Regression model with high R-squared or a low RMSE value. Linear Regression works on some key assumptions: ...
Recent Posts
How to Interpret Regression Analysis Results: P-values and Coefficients
Linear Regression is much more than just using scikit-learn’s fit & predict function. If you use Statsmodels API for Linear Regression, you will get a c...
Understanding the use of any() and all() in NumPy arrays
If you get this Value error in numpy The truth value of an array with more than one element is ambiguous. Use a.any() or a.all(). In this Numpy tutorial, I w...
Chi-Squared For Feature Selection using SelectKBest
We calculate Chi-square between each feature & the target & select the desired number of features with best Chi-square scores or the lowest p-values...
How to upload your python package to PyPi using Twine
Make your code publish-ready Refer to the following blog for understanding how you need to structure your python projects. Create a python package In...