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blending

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Build a predictive machine learning model that could categorize users as either, revenue generating, and non-revenue generating based on their behavior while navigating a website. In order to predict the purchasing intention of the visitor, aggregated page view data kept track during the visit along with some session is used and user information as input to machine learning algorithms. Oversampling/Undersampling and feature selection techniques are applied to improve the success rates and scalability of the models.

  • Updated Mar 24, 2021
  • Jupyter Notebook

Boolean Logic Data Prep, Text and Dates, Unions, Joins and Blending, Parameters and Sets, Level of Details, LOD Calculations, Animations, New Visualizations: Funnel Graphs, Gantt Charts, Bump, Donut, Packed Bubbles, Waterfall Chart, London Pathways, , Branches, Multiple Outputs, Outputiing, CSV, Hyper, Preview, Cleaning Text, Unpivotting, ETL, Extract, Transform and Load: Unios, Join, Multi-Joins, If functions, Concatenate, Date Functions, Find and Replace, Desktop Specialist Certification, Desktop Certified Associate, Desktop Certified Professional.

  • Updated Dec 31, 2021

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