Banknote Authentication: Machine Learning Classification in Python Step by Step скачать в хорошем качестве

Banknote Authentication: Machine Learning Classification in Python Step by Step

Learn how to build and evaluate machine learning models to detect real vs fake banknotes using Python. This lesson covers practical data loading, feature exploration, model training, error handling, and best practices for banknote authentication. Load the banknote authentication dataset from OpenML with pandas. Explore dataset structure, data types, and basic statistics for four numerical features. Visualize class distribution and feature distributions using countplots, histograms, and boxplots. Split data into training and test sets and prevent data leakage. Train a logistic regression classifier, evaluate accuracy, and interpret the confusion matrix. Investigate feature correlations and visualize with a heatmap. Build and assess a Random Forest model, comparing accuracy and examining feature importances. Demonstrate error handling with data type issues and walk through cleanup steps. #machinelearning #python #banknoteauthentication