Book Prices Prediction

Contents

Data Understanding

Understanding data and features

Data Cleaning For EDA

• Renaming columns
• Categorical to numerical
• Feature expansion
• Feature extraction
• Null values handling

Exploratory Data Analysis

• Univariate Analysis

  • Target analysis
  • Numerical features
  • Categorical features

• Bivariate Analysis

  • Year analysis
  • Population analysis
  • Price analysis

Data Preprocessing

• Target Log

• Encoding

  • Ordinal
  • One Hot
  • Count Vectorizer

• Discretization

• Normalization

• Scaling

• Standardization

• Outlier Detection

Modeling

Random forest regressor is used.

Evaluation

MSE for train and test datasets

• Train MSE

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• Test MSE

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Feature Importance