Michigan Covid-19 prediction
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Updated
Feb 27, 2024 - HTML
Michigan Covid-19 prediction
In this project I use unsupervised learning techniques to identify different segments of costumers with different preferences for optimizing product delivery.
Final project Of machine learning Nanodegree (Unsupervised Learning)
Project - Creating customer segments | Unsupervised learning | Python | PCA | Gaussian Mixture Model
Udacity Machine Learning Engineer Nanodegree Unsupervised Learning Project: Creating Customer Segments
PCA and Gaussian Mixture Model Clustering to uncover hidden segments in customer purchase data.
The project explores KMeans and Gaussian Mixture Algorithms to classify the Boston Housing Dataset into different groups based on different parameters.
In this project I have used unsupervised learning techniques to see if any similarities exist between customers, and how to best segment customers into distinct categories using a real-world dataset
Unsupervised Learning: Mixture of Balls With Different Volumes.
Customer Segments - Machine Learning Nanodegree from Udacity
Use the credit card customer database to segement the groups by taking into account their spending patterns as well as past interactions with the bank
Unsupervised clustering of the UCI Wholesale Customer Spending Dataset
Processing scripts and datasets for a project on medial vowels in Kaytetye
Unsupervised Learning ML project
An ML model which uses Gaussian Mixture Model clustering to classify customers.
Partial Label Learning based on GMM
Applied Unsupervised Learning techniques on product spending data collected for customers of a wholesale distributor to identify customer segments hidden in the data.
Bundle Adjustment for Close-Range Photogrammetry
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