Find community/segment in an attributed graph of Facebook data.
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Updated
Apr 20, 2017 - Python
Find community/segment in an attributed graph of Facebook data.
Comprehensive EDA and market analysis of the automotive industry. Implements advanced feature engineering, statistical modeling (HP/Price correlation), and interactive Power BI visualizations to identify luxury vs. mainstream market bifurcations.
Electric Vehicle Market Segmentation Analysis in India
Big Data Analytics [BDA] Mini Project
Identify commercial centers using Points of Interest (POI) data by clustering these points into commercial centers/markets
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A customer segmentation project.
Implementation of a d3.js Visual Analytics dashboard for Sales Analysis and Customer Segmentation in Retail
This repository contains the market cluster analysis performed on the Philippine's demographic data using JMP by SAS.
Unsupervised Learning Projects – Research-oriented Python portfolio exploring clustering, customer segmentation, pattern discovery, and evaluation on real-world datasets using KMeans, DBSCAN, Agglomerative, and divisive methods.
Bayesian Market Segmentation Algorithm for Hedonic Analysis
Clustering the Mall customers to analyze the different market segments of the Mall
The food aggregator company has stored the data of the different orders made by the registered customers in their online portal. Identify areas of growth and improvement for a better customer experience.
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Notebook to Perform Market Segmentation using K-means clustering, PCA, and Auto-encoders.
A machine learning project to replicate a market segmentation case study on McDonald's customers using clustering techniques, powered by Python and scikit-learn.
The beverage choice that accompanies most American pastime is divided between 🍺 Beer and 🥤 Soda. A market segmentation is performed to study this division - brands, demographic, profit - with the goal of target marketing.
Unsupervised clustering analysis of vehicle specifications using Hierarchical and K-Means methods (educational dataset).
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