Machine Learning for Heart Disease Prediction

Project Overview:

I am looking for a freelancer to develop a Heart Disease Prediction Analysis project using Python and Machine Learning.

Requirements:

Perform data cleaning and preprocessing
Handle missing values and duplicates
Perform Exploratory Data Analysis (EDA)
Create meaningful visualizations using Matplotlib and Seaborn
Analyze correlations and important features
Build and compare at least 3 classification models:
Logistic Regression
Decision Tree
Random Forest
Evaluate models using:
Accuracy
Precision
Recall
F1-Score
Confusion Matrix
ROC-AUC
Include a sample prediction using the best-performing model
Provide a clear final conclusion and model comparison

Deliverables:

Complete Jupyter Notebook (.ipynb)
Clean and commented Python code
EDA visualizations
Machine learning models and evaluation
Model comparison
Sample prediction
Final findings and conclusion
README/instructions if required

Important:

This is an academic/educational project only. The model should not be considered a medical diagnostic or clinical decision-making tool.

Please apply only if you have experience with Python, Machine Learning, Data Analysis, EDA, and Scikit-learn.