SMRodrigo96 / Data-Science-Project-

Benchmarking bank data to enhance marketing strategies. Models: Decision Tree and Random Forest. Libraries: Pandas, Matplotlib, Seaborn, Scikit-Learn, Numpy. Findings: Customer patterns and seasonal behaviors.

Data Scientist Project, Dataset: "Bank-Marketing-Data"

This project was created with the goal of honing programming skills and developing proficiency as a data analyst, contributing to the professional growth toward a career as a Data Scientist.

Description

The project serves as a practice ground for various programming and data analysis techniques. It explores different aspects of data science, offering hands-on experience in solving real-world problems. As part of the learning journey, the project may cover topics such as data manipulation, analysis, visualization, and more.

Technologies Used

. Python . Libraries: Pandas, NumPy, Matplotlib, Seaborn, Scikit-Learn Among ohters

Link Dataset UCI Machine Learning Repository URL: https://archive.ics.uci.edu/ml/datasets/Bank+Marketing