CustomerInsight-AI
CustomerInsight-AI is a supervised machine-learning project focused on loan approval prediction. The project processes a dataset containing 1,000 entries and 18 original features, performs preprocessing and exploratory data analysis, and benchmarks multiple classification algorithms. Logistic Regression, K-Nearest Neighbors and Naive Bayes are trained on the same preprocessed dataset and evaluated using Precision, Accuracy, Recall and F1-Score.
Category
Machine Learning
Environment
Jupyter Notebook
Language
Python
Status
Completed
01 / Overview
Predicting loan approval with machine learning.
An end-to-end classification project covering data preprocessing, exploratory data analysis, feature transformation, model training and performance evaluation.
02 / Workflow
Project pipeline.
Dataset
Loan application data with 1,000 entries and 18 original features prepared for analysis.
Preprocessing
Missing values handled, categorical features encoded and numerical features scaled.
Feature Engineering
Non-predictive attributes removed and features transformed for classification.
Model Training
KNN, Logistic Regression and Naive Bayes trained and evaluated on the processed dataset.
Model Laboratory
Classification
experiments.
Logistic Regression
LRK-Nearest Neighbors
KNNNaive Bayes
NBTechnology Stack
01
Python
02
Pandas
03
Scikit-learn
04
Jupyter Notebook
Gallery
Project visuals.
End of project