customer-segments

There are 2 repositories under customer-segments topic.

Acrotrend / Awesome-Customer-Analytics
A curated list of awesome customer analytics content
customer-segments case-study text-analysis
95
klaudia-nazarko / rfm-analysis-python
This repository contains RFM analysis applied to identify customer segments for global retail company and to understand how those groups differ from each other.
python rfm-analysis retail-data customer-segmentation customer-segments data-science
Language:Jupyter Notebook 27
DionysiosZelios / RFM_analysis
RFM (Recency, Frequency, Monetary) analysis is a proven marketing model for behavior based customer segmentation. It groups customers based on their transaction history – how recently, how often and how much did they buy. RFM helps divide customers into various categories or clusters to identify customers who are more likely to respond to promotions and also for future personalization services.
rfm-analysis segmentation rfm customer-segments email-marketing-campaigns
Language:Jupyter Notebook 24
marcotav / unsupervised-learning
This repo contains unsupervised models including the Latent Dirichlet Allocation (LDA) model applied to a corpus of research papers and a clustering analysis applied to customer segmentation.
clustering topic-modeling customer-segments research-paper pyldavis lda
Language:Jupyter Notebook 18
SagarPatel98 / Customer-Segmentation-using-Machine-Learning
This project is based on Unsupervised Learning
customer-segments clustering unsupervised-learning dataset clustering-model machine-learning
Language:Jupyter Notebook 16
jjone36 / Cohort
Customer Segmentation Anaylsis
customer-segments cohort customer-segmentation-analysis marketing rfm-values data-analysis visualization
Language:Jupyter Notebook 10
RFM-Model
fvanheer / RFM-Model
Basic RFM model to kickstart customer value segmentation. This project aims to guide the first time user to have a bouncing board into setting up their first segmentation model.
rfm-analysis customer-segments streamlit dashboard-application statistical-analysis python3
Language:Python 9
JuzerShakir / Creating-Customer-Segments
Applied Unsupervised Learning techniques on product spending data collected for customers of a wholesale distributor to identify customer segments hidden in the data.
unsupervised-learning machine-learning-nanodegree udacity classification pca customer-segments k-means-clustering python pandas data-visualization data-exploration silhouette gaussian-mixture-models numpy matplotlib scikit-learn seaborn feature-selection machine-learning-tutorials unsupervised-machine-learning
Language:HTML 3
mayur29 / Udacity_Machine_Learning_Projects
These are all the assignments from Udacity Nanodegree Machine Learning course
udacity-machine-learning-nanodegree boston-housing-price-prediction customer-segments dog-breed-classifier udacity-course udacity-nanodegree energy-efficiency energy-monitor capstone-project appliance-monitor udacity-machine-learning
Language:Jupyter Notebook 3
nano-bot01 / Customer-Segmentation-using-Clustering-
Customer Segmentation using Clustering (Machine Learning)
ankit-nainwal clustering clustering-algorithm customer-segmentation customer-segmentation-analysis customer-segments jupyter-notebook k-means k-means-clustering k-means-implementation-in-python machine-learning machine-learning-algorithms ml ml-models nano-bot01 segmentation
Language:Jupyter Notebook 3
alimdsaif3 / Customer_Segmentation_for_Retail_Shop
Customer segmentation is a process where we divide the consumer base of the company into subgroups. We need to generate the subgroups by using some specific characteristics so that the company sells more products with less marketing expenditure.
customer-segments consumer-subgroup marketing
Language:Jupyter Notebook 2
cakmakaf / customer_segmentation
We apply PCA transformations to the data and implement clustering algorithms to segment the transformed customer data
unsupervised-learning pca-analysis customer-segments numpy scikit-learn
Language:Jupyter Notebook 2
SKRohit / Customer_Segmentation
Code to perform clustering using self organizing maps on retail customer data.
clustering customer-segments hierarchical-clustering som
Language:Python 2
haataa / Identify_Customer_Segments
This project identify segments of the population that form the core customer base for a mail-order sales company in Germany. These segments can then be used to direct marketing campaigns towards audiences that will have the highest expected rate of returns. The data has been provided by Bertelsmann Arvato Analytics.
machine-learning clustering pca customer-segments data-science
Language:Jupyter Notebook 1
moreirab / customer-segments
Machine Learning Engineer Nanodegree, Unsupervised Learning, Creating Customer Segments
biplot clustering clustering-algorithm customer-segmentation customer-segments data-recovery data-visualization dimensionality-reduction feature-scaling feature-transformation gaussian-mixture-model gmm k-means-clustering pca principal-component-analysis segmentation udacity udacity-machine-learning-nanodegree udacity-nanodegree unsupervised-learning
Language:HTML 1
Venka97 / Customer-segments
This project uses unsupervised learning techniques and decomposition methods to find meaningful structure in the data.
clustering customer-segments machine-learning udacity-nanodegree unsupervised-learning
Language:Jupyter Notebook 1
adityasahastrabudhe01 / customer_segments
Udacity Machine Learning Engineer Nanodegree Unsupervised Learning Project: Creating Customer Segments
udacity udacity-machine-learning-nanodegree python jupyter-notebook customer-segments clustering-algorithm pca gaussian-mixture-models unsupervised-learning machine-learning
Language:HTML 0
ashva7 / customer_segments
Customer Segments - Machine Learning Nanodegree from Udacity
biplot clustering customer-segments dimensionality-reduction feature-transformation gaussian-mixture-models heatmap k-means k-means-clustering machine-learning machine-learning-algorithms outlier-detection pca pca-analysis scatter-matrix udacity udacity-machine-learning-nanodegree udacity-nanodegree unsupervised-learning unsupervised-machine-learning
Language:HTML 0
jetjodh / customer_segments
Project done in ML course
customer-segments python jupyter-notebook machine-learning udacity-nanodegree
Language:HTML 0
mmuppidi / customer_segments
Project: Creating Customer Segments using Unsupervised Learning
udacity-machine-learning-nanodegree customer-segments unsupervised-learning
Language:Jupyter Notebook 0
NoreenMekky / customer_segments
udacity udacity-machine-learning-nanodegree customer-segments unsupervised-machine-learning
Language:Jupyter Notebook 0
vishwasourab / customer_segmentation
In this project, I will analyze a dataset containing data on various customers' annual spending amounts (reported in monetary units) of diverse product categories for internal structure. One goal of this project is to best describe the variation in the different types of customers that a wholesale distributor interacts with. Doing so would equip the distributor with insight into how to best structure their delivery service to meet the needs of each customer.
segmentation customer-segments unsupervised-learning machine-learning clustering kmeans-clustering python notebook
Language:HTML 0
ymubarak / Machine_Learning_Nanodegree
Projects of Udacity's Machine Learning Specialization Nanodegree program.
machine-learning machine-learning-nanodegree python deep-learning supervised-learning unsupervised-learning reinforcement-learning boston-housing classify-dog-breeds smartcab titanic-passengers customer-segments
Language:Jupyter Notebook 0
anshulika-prasad / udacity-ML-customer-segments
My final submitted project for udacity basic ML course, customer segments
sklearn desiciontree udacity-nanodegree customer-segments gaussian-mixture-models k-means
Language:Jupyter Notebook
josancamon19 / customer_segments
Creating Customer Segments for Udacity Machine Learning Engineer Nanodegree
machine-learning udacity machine-learning-nanodegree customer-segments
Language:Jupyter Notebook
Mazen-Embaby / customer_segments
In this project, you will work with real-life data provided to us by our Bertelsmann partners AZ Direct and Arvato Finance Solution. The data here concerns a company that performs mail-order sales in Germany. Their main question of interest is to identify facets of the population that are most likely to be purchasers of their products for a mailout campaign. Your job as a data scientist will be to use unsupervised learning techniques to organize the general population into clusters, then use those clusters to see which of them comprise the main user base for the company. Prior to applying the machine learning methods, you will also need to assess and clean the data in order to convert the data into a usable form.
customer-segments tensorflow jyputer-notebook
Language:HTML
sanjeevai / customer_segments
Reviewed unstructured data to understand the patterns and natural categories that the data fits into. Made predictions about the natural categories of multiple types in a dataset, then checked these predictions against the result of unsupervised analysis.
customer-segments unsupervised-learning cluster-data natural-categories prediction sklearn data-visualisation pca ica feature-selection
Language:HTML

customer-segments

Acrotrend / Awesome-Customer-Analytics

klaudia-nazarko / rfm-analysis-python

DionysiosZelios / RFM_analysis

marcotav / unsupervised-learning

SagarPatel98 / Customer-Segmentation-using-Machine-Learning

jjone36 / Cohort

fvanheer / RFM-Model

JuzerShakir / Creating-Customer-Segments

mayur29 / Udacity_Machine_Learning_Projects

nano-bot01 / Customer-Segmentation-using-Clustering-

alimdsaif3 / Customer_Segmentation_for_Retail_Shop

cakmakaf / customer_segmentation

SKRohit / Customer_Segmentation

haataa / Identify_Customer_Segments

moreirab / customer-segments

Venka97 / Customer-segments

adityasahastrabudhe01 / customer_segments

ashva7 / customer_segments

jetjodh / customer_segments

mmuppidi / customer_segments

NoreenMekky / customer_segments

vishwasourab / customer_segmentation

ymubarak / Machine_Learning_Nanodegree

anshulika-prasad / udacity-ML-customer-segments

josancamon19 / customer_segments

Mazen-Embaby / customer_segments

sanjeevai / customer_segments