Machine Learning/Pattern Recognition Models to analyze and predict if a client will subscribe for a term deposit given his/her marketing campaign related data
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Updated
Jun 5, 2018 - Python
Machine Learning/Pattern Recognition Models to analyze and predict if a client will subscribe for a term deposit given his/her marketing campaign related data
These projects as a part of my Data Science internship involve data visualisation, analysis, & prediction using various datasets and machine learning techniques. They utilize libraries like pandas, matplotlib, seaborn, scikit-learn, and NLTK for tasks ranging from gender and age visualisation to sentiment analysis and decision tree classification.
This repository contains a Python script that analyzes the "Bank Marketing" dataset from the UCI Machine Learning Repository. The primary goal is to predict whether a client will subscribe to a term deposit based on various features using a Decision Tree Classifier.
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