Heart Disease Prediction with Decision Tree | Python Tutorial

Welcome to our in-depth tutorial on predicting heart disease using decision tree classification! In this video, we'll walk you through the entire process, from data preprocessing to model evaluation and visualization. Whether you're a beginner or an experienced data scientist, this tutorial will provide valuable insights into using decision trees for classification tasks.
📌 Topics Covered:
Introduction to Decision Trees
Data Preprocessing Steps
Feature Selection
Building the Decision Tree Model
Evaluating Model Performance
Visualizing Actual vs. Predicted Results
📊 Dataset: Heart Disease Data
📈 Tools: Python, Pandas, Scikit-learn, Matplotlib
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[@aishusamazingworld]

Do we need to convert float dtypes column into int dtype.

[@AnalystChronicles]

conversions are situational, depending on the nature of your data and the transformations you're applying during preprocessing.