/MachineLearning-Marketing-Department

The project is aimed to help New York City Bank marketing team to launch a targeted ad marketing campaign by dividing their customers into at least 3 distinctive groups. The bank has extensive data on their customers for the past 6 months.

Primary LanguageJupyter Notebook

Machine Learning for Marketing Department Case Studies

Project Highlights:

  1. Conducted Exploratory Data Analysis using distplot, histogram, and KDE
  2. Solved missing data issue
  3. Established how to find the optimal number of clusters using elbow method
  4. Applied K Means in scikit learn to perform market segmentation
  5. Built and trained autoencoder models in keras
  6. Applied PCA to perform dimensionality reduction using real world dataset