@khurshidrpvv wrote:
I am new to data science.I am not able to understand how our model learns with the data set.Means to say, when we perform data munging and related stuff,in the end we eliminate some columns from the data set.
what I think is that we eliminate all redundant rows and columns which we think will not add up in decision making and in order to make our model learn we leave our train data with only those rows and columns that we think will provide a positive result.whenever I googled I ended up with machine learning algorithms.I need to know the basic idea about predictive modeling irrespective of the chosen algorithm
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