Level Based Customer Segmentation

Last update: Dec 21, 2021

Overview

level_based_customer_segmentation

Level Based Customer Segmentation Persona Veri Seti kullanılarak müşteri segmentasyonu yapılmıştır.

KOLONLAR :

PRICE – Müşterinin harcama tutarı
SOURCE – Müşterinin bağlandığı cihaz türü
SEX – Müşterinin cinsiyeti
COUNTRY – Müşterinin ülkesi AGE – Müşterinin yaşı

ADIMLAR:

Yaş değişkeni binleri içerecek şekilde kategorikleştirilmiştir.
Seviye tabanlı müşterileri (persona) tanımları yapılmıştır.
Price değişkeni kullanılarak müşterilere 4 segmente [A, B, C, D] ayrılmıştır.
Yeni gelen müşteri için segment tahmini yapılmıştır.

Owner

Buse Yıldırım

GitHub Repository

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Level Based Customer Segmentation

Related tags

Overview

level_based_customer_segmentation

Owner

Buse Yıldırım

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Level Based Customer Segmentation

Related tags

Overview

level_based_customer_segmentation

Owner

Buse Yıldırım

Blender Add-on that sets a Material's Base Color to one of Pantone's Colors of the Year

Deeprl - Standard DQN and dueling network for simple games

Pytorch code for "State-only Imitation with Transition Dynamics Mismatch" (ICLR 2020)

Scripts for training an AI to play the endless runner Subway Surfers using a supervised machine learning approach by imitation and a convolutional neural network (CNN) for image classification

Python periodic table module

Which Style Makes Me Attractive? Interpretable Control Discovery and Counterfactual Explanation on StyleGAN

Music library streaming app written in Flask & VueJS

[Preprint] "Bag of Tricks for Training Deeper Graph Neural Networks A Comprehensive Benchmark Study" by Tianlong Chen*, Kaixiong Zhou*, Keyu Duan, Wenqing Zheng, Peihao Wang, Xia Hu, Zhangyang Wang

Lepard: Learning Partial point cloud matching in Rigid and Deformable scenes

git《Joint Entity and Relation Extraction with Set Prediction Networks》(2020) GitHub:

TorchGeo is a PyTorch domain library, similar to torchvision, that provides datasets, transforms, samplers, and pre-trained models specific to geospatial data.

Progressive Image Deraining Networks: A Better and Simpler Baseline

Yolov5+SlowFast: Realtime Action Detection Based on PytorchVideo

The codes of paper 'Active-LATHE: An Active Learning Algorithm for Boosting the Error exponent for Learning Homogeneous Ising Trees'

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