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Book price dataset analysis and modeling

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bivariate-analysis eda feature-engineering feature-extraction feature-importance nlp one-hot-encoding ordinal-encoding outlier-detection random-forest-regressor scaling univariate-analysis

book-price-prediction's Introduction

Book Prices Prediction

Contents

Data Understanding

Understanding data and features

info

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

  • tr

  • Test MSE

  • te

Feature Importance

f

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