Customer Segmentation using Machine Learning
This project aims to build a model which is able to predict whether the customer is a potential one or not for the Business
8 Hrs. | Intermediate
INR 0
This Course Includes:
- 30 Days Access to Workspace
- Dedicated Mentor Support
- Project Resources & References
- Project Completion Certificate
Skills you will develop
- Python
- Python Web Frame works
- Python For data Analysis
- Python For data Visualization
- Data Preprocessing Techniques
- Machine Learning
Project Description
Introduction :
In today’s highly competitive world, the primal aim of any business is to grab potential customers who can generate profits for the organization. With increasing the number of organizations in the market, companies want to gain a competitive advantage over others.
The primal task of Management is to identify potential customers from the rest. This will be simplified with the help of Machine Learning models to classify the customers into segments based on various attributes.
The intervention of Data Science and AI helps the business to build such models to analyze the customers and their products in better decision making, to improvise the business process, to formulate better strategies, and to improve the revenue.
This project deals with understanding and segmenting the customers based on the data.
The Model we built will be able to classify the customer’s potentiality in purchasing power.
We will be using classification algorithms such as H-clustering, k-means clustering Decision tree, Random forest, KNN, and xgboost. We will train and test the data with these algorithms. From this best model is selected and saved in pkl format. Once the model is saved, we integrate it with the flask application and also deploy the model in IBM.
The primal task of Management is to identify potential customers from the rest. This will be simplified with the help of Machine Learning models to classify the customers into segments based on various attributes.
The intervention of Data Science and AI helps the business to build such models to analyze the customers and their products in better decision making, to improvise the business process, to formulate better strategies, and to improve the revenue.
This project deals with understanding and segmenting the customers based on the data.
The Model we built will be able to classify the customer’s potentiality in purchasing power.
We will be using classification algorithms such as H-clustering, k-means clustering Decision tree, Random forest, KNN, and xgboost. We will train and test the data with these algorithms. From this best model is selected and saved in pkl format. Once the model is saved, we integrate it with the flask application and also deploy the model in IBM.
Technical Architecture:
