Project 4: Unsupervised Learning

Project 4: Unsupervised Learning

Clustering Analysis of Customer Segments

Project Description:

You are given a dataset containing customer information for an online store. The objective of this project is to apply clustering algorithms to identify different customer segments based on their purchase behavior. You will need to preprocess the data, apply different clustering algorithms, and evaluate their performance. You will also need to interpret the results and provide recommendations for the online store to improve their sales strategy.

Tasks:

1. Load the dataset and perform exploratory data analysis to gain insights into the data
2. Preprocess the data by cleaning, normalizing, and transforming the features as required
3. Apply k-means, hierarchical clustering, and density-based clustering algorithms to identify customer segments
4. Evaluate the performance of the clustering algorithms using appropriate metrics
5. Interpret the results and provide recommendations for the online store to improve their sales strategy

Deliverables:

1. Jupyter notebook containing the code for preprocessing, clustering, and evaluation
2. A report summarizing the insights gained from the analysis, the performance of the different clustering algorithms, and the recommendations for the online store.

Dataset: 

The dataset is available at: https://archive.ics.uci.edu/ml/datasets/online+retail

Note: 

You may use any programming language and clustering libraries of your choice.