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Market-Segmentation-Analysis

Perform detailed analysis on customer data to segment markets, enabling targeted marketing strategies for improved conversion rates on various products.

CASE STUDY: MARKETING DEPARTMENT

Key Learning Outcomes:

  • Understand how to leverage the power of data science to perform market segmentation and transform marketing department.
  • Perform exploratory data analysis and visualize customers dataset using distplot, histograms and KDE.
  • Learn how to fill out missing data points (null elements).
  • Understand the theory and intuition behind K means clustering algorithms.
  • Learn how to find the optimal number of clusters using the elbow method.
  • Apply K means algorithms in Scikit learn to perform market segmentation.
  • Understand the theory and intuition behind autoencoders.
  • Learn auto encoders to perform dimensionality reduction.
  • Build and train autoencoder models in keras.
  • Understand the intuition behind principal components analysis (PCA).
  • Apply PCA to perform dimensionality reduction using real world datasets.

  • Marketing + Unsupervised learning + Kmeans + Elbow method + Autoencoders + PCA

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Perform detailed analysis on customer data to segment markets, enabling targeted marketing strategies for improved conversion rates on various products.

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