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Data Science in Python: Classification Modeling

Udemy
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Data Science in Python: Classification Modeling

Data Science in Python: Classification Modeling Course

Learn Python for Data Science & Supervised Machine Learning, and build classification models with fun, hands-on projects

This Data Science in Python: Classification Modeling Udemy Course Created by Maven Analytics and Chris Bruehl with 10 hours on-demand video, 3 articles, 2 downloadable resources and Certificate of completion. This is a hands-on, project-based course designed to help you master the foundations for classification modeling in Python.

What you’ll learn

  • Master the foundations of supervised Machine Learning & classification modeling in Python
  • Perform exploratory data analysis on model features and targets
  • Apply feature engineering techniques and split the data into training, test and validation sets
  • Build and interpret k-nearest neighbors and logistic regression models using scikit-learn
  • Evaluate model performance using tools like confusion matrices and metrics like accuracy, precision, recall, and F1
  • Learn techniques for modeling imbalanced data, including threshold tuning, sampling methods, and adjusting class weights
  • Build, tune, and evaluate decision tree models for classification, including advanced ensemble models like random forests and gradient boosted machines

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