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      Question

      'Exploratory Data Analysis' (EDA)

      involves:
      A Building the final predictive model using the cleaned dataset Correct Answer Incorrect Answer
      B Deploying a fully functional machine learning model to a production environment for prediction, classification or clustering Correct Answer Incorrect Answer
      C Systematically analysing datasets to understand patterns, detect anomalies, test assumptions, and identify relationships Correct Answer Incorrect Answer
      D Collecting raw data from various source systems using API calls and storing them in a data warehouse Correct Answer Incorrect Answer
      E Optimizing database query performance for analytical workloads Correct Answer Incorrect Answer

      Solution

      EDA (pioneered by John Tukey) involves univariate analysis (distributions, histograms, box plots), bivariate analysis (correlation matrices, scatter plots), multivariate analysis, missing value analysis, outlier detection, skewness/kurtosis examination, and feature relationship exploration. EDA informs feature engineering, model selection, and data cleaning decisions. In banking, EDA on loan application data might reveal that income-to-EMI ratio is highly correlated with default which is a critical feature to include in the credit model. Tools used for EDA include Pandas Profiling, Seaborn, Matplotlib and Plotly.

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