Welcome to my submission for Task 3 of the Data Science Internship at Prodigy Infotech. In this task, I have Build a Dicision tree classifier to predict whether a customer will purchase a product or service based on their demographic and behavioral data.
The dataset used for this task is Bank_dataset. This repository contains the Bank dataset, which includes customers information and the features attributes such as customers demographics, and Customers behavioral data.
- Jupyter notebook
- Pandas
- Numpy
- Matplotlip & Seaborn for visualization
- scikit learn
During the Dicision Tree Classifier, I performed the following steps:
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Data Cleaning: Checked for missing values, duplicates, and outliers in the dataset and handled them accordingly.
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Visualization: Created a Dicision Tree, Histogram Plot, Count Plot, Plot to Explore the Data and Predict the purchasing Behavioral patterns of the customers.
In this project, you effectively leveraged a Decision Tree classifier to analyze and predict customer purchasing behavior. The use of the Bank dataset provided a rich set of features for your model. By successfully implementing this classifier, you can gain insights into which factors influence purchasing decisions, potentially guiding marketing strategies and improving customer engagement.
Overall, this project showcases your skills in applying machine learning techniques to real-world datasets, providing practical insights that can benefit business decisions.
Thank you for reviewing my submission!
For any inquiries or feedback regarding this project, please contact: