When you are given a dataset in Machine learning Interview, you have to do the exploratory data analysis. Exploratory data analysis includes variable identification, univariate and bivariate analysis, check for missing values and outliers. After these steps look for feature engineering i.e. create new variables from existing variables, removing unnecessary variables. After EDA and feature engineering built an ML model and check the performance metrics to validate the model.
I would suggest going through this blog on Machine Learning Interview Questions that cover frequently asked questions in Machine learning Interviews of top companies.
You can watch this video for most frequently asked questions in the Machine learning interview:
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