Feature selection


In this topic  will focus on one of the 2 critical parts of getting your models right – feature selection also will discuss in detail why feature selection plays such a vital role in creating an effective predictive model.

https://www.analyticsvidhya.com/blog/2016/12/introduction-to-feature-selection-methods-with-an-example-or-how-to-select-the-right-variables/


ANOVA


In this topic you will get a overview of how to select features using the ANOVA(f-regressor).

https://www.youtube.com/watch?v=-yQb_ZJnFXw


PCA(Principal component Analysis)


This very interesting part. In this topic you will get to know the Making sense of principal component analysis, eigenvectors & eigenvalues from very basic point of view.

https://stats.stackexchange.com/questions/2691/making-sense-of-principal-component-analysis-eigenvectors-eigenvalues


https://towardsdatascience.com/a-one-stop-shop-for-principal-component-analysis-5582fb7e0a9c