Common mistakes made in Machine Learning Models

IN this video you will learn the common mistake people make while building machine learning models .

Machine learning models are easy to build but need attention to details.

The common mistakes could be :

1- taking Default Loss Function for granted

2- Using one Algorithm / Method For All Problems:

3- Ignoring Outliers:

4- No Proper Dealing With Cyclical Features

5- L1/L2 Regularisation Without Standardisation

6- Interpreting Coefficients From Linear or Logistic Regressions as features importance

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