@AUTHOR: RAHUL SINGH
Benefit of EDA is to refine your selection of feature variables that will be used later for machine learning. Once you gain deep familiarity with your data set, you may need to revisit the feature engineering step – you may find the features you selected do not serve their intended purpose. Moreover you may discover other features that add to the overall picture the data presents. Once you complete the EDA stage you should have a firm feature set with which to use for supervised and unsupervised statistical learning.
In a hurry to get to the machine learning stage, some data scientists either entirely skip the exploratory process or do a very perfunctory job. This is a mistake with many implications, including generating inaccurate models, generating accurate models but on the wrong data, not creating the right types of variables in data preparation, and using resources inefficiently because of realizing only after generating models that perhaps the data is skewed, or has outliers, or has too many missing values, or finding that some values are inconsistent.
Here with the help of AUTO EASY EDA APP we can do EDA within few minutes. It saves times and most Important its just drag and dropping of files.
