Data Science anda Heart Diseases

Elucidated the life cycle of any DataScience Project with the help of two Dataset, namely :

Sections

✔️ Data Analysis

  • Missing / Duplicate Values
  • Find all the Continuous Features
  • Handling Outliers if Any
  • Distribution of the Continuous Features
  • Find all the Discrete Features
  • Cardinality of Discrete Features
  • Relation with Independent and Dependent Features

✔️ Feature Engineering

  • Dealing with Missing Values
  • Feature Selection
  • One-Hot Encoding
  • Feature Scaling

✔️ Modeling

  • K-Nearest Neighbors
  • Random Forest
  • Logistic Regression with L1 Penalty
  • Logistic Regression with L2 Penalty
  • Logistic Regression with Elasticnet Penalty

✔️ HyperParameter Tuning

  • GridSearchCV

✔️ Model Evaulation

  • Train-Test Split VS K-Fold
  • Classification Report (precision, recall, f1-score, support)
  • Confusion_matrix

Demo : https://rstak.github.io/Data-Science-and-Heart-Diseases/

Project link: https://github.com/RsTaK/Data-Science-and-Heart-Diseases