Data Science, Machine Learning, and Statistical Analysis
Businesses have vast amounts of customer data, but without proper analysis, this data is underutilized. Customer segmentation helps classify customers into different groups based on their preferences, spending habits, and demographics. In this project, machine learning techniques such as K-Means Clustering, Hierarchical Clustering, and DBSCAN will be used to segment customers based on available data. The goal is to provide businesses with insights that can help in targeted marketing, personalized recommendations, and customer retention strategies.
Programming Languages: Python, R, SQL Libraries: Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn, TensorFlow/Keras (if deep learning is used) Software/Tools: Jupyter Notebook, Google Colab, Tableau/Power BI (for visualization), PostgreSQL/MySQL (for data storage) Before Commencing the project the following links have to be examined.
https://www.kaggle.com/
https://archive.ics.uci.edu/
https://dataverse.harvard.edu/
https://datasetsearch.research.google.com/
